The pursuit of sustainable energy production through the conversion of agricultural waste into different bioenergy resources is of paramount importance given its potential to mitigate environmental impact while meeting energy demands. In this review, a comprehensive overview of the technologies for the biochemical and thermochemical conversion of agricultural waste into bioenergy is provided. A summary of the process of its conversion into different bioenergy products such as biogas, bio-oil, and biofuel is provided, in addition to the potential advantages and challenges faced using different biomass conversion technologies. The review highlights the potential of agricultural waste valorization to address the current energy demand while at the same time contributing to environmental benefits and greenhouse gas emission reductions. Moreover, this review highlights some significant gaps for improvement. These include the challenges in the pretreatment of agricultural waste biomass in optimizing the conversion rates and lowering the required energy consumption throughout the process while enhancing both the quantity and quality of the output. Some recommendations are proposed to address the identified challenges. These include the need for further studies for a thorough assessment to evaluate the efficacity and sustainability of agricultural waste valorization technologies. Assessment methods such as life cycle assessment (LCA), life cycle analysis (LCA), net energy ratio (NER) calculations, life cycle costing (LCC), as well as techno-economic assessment (TEA), are recommended, together with collaboration among governments, farmers, and researchers, as well as the integration of cutting-edge technologies to enhance various aspects of agricultural waste, optimizing the conversion process, cost efficiency, time management, and labor requirements, consequently boosting the conversion efficiency and product quality.

Lignin is a natural biopolymer. A vibrant and rapid process in the synthesis of silica nanoparticles by consuming the lignin as a soft template was carefully studied. The extracted biopolymer from coir pith was employed as capping and stabilizing agents to fabricate the silica nanoparticles (_nSi). The synthesized silica nanoparticles (_nSi) were characterized by ultraviolet–visible (UV–Vis) spectrophotometry, X-ray diffraction analysis (XRD), Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Analysis (EDAX), Dynamic Light Scattering (DLS) and Fourier-Transform Infrared Spectroscopy (FTIR). All the results obtained jointly and independently verified the formation of silica nanoparticles. In addition, EDAX analysis confirmed the high purity of the _nSi composed only of Si and O, with no other impurities. XRD spectroscopy showed the characteristic diffraction peaks for _nSi and confirmed the formation of an amorphous nature. The average size of _nSi obtained is 18 nm. The surface charge and stability of _nSi were analyzed by using the dynamic light scattering (DLS) and thus revealed that the _nSi samples have a negative charge (−20.3 mV). In addition, the seed germination and the shoot and root formation on Vigna unguiculata were investigated by using the _nSi. The results revealed that the application of _nSi enhanced the germination in V. unguiculata. However, further research studies must be performed in order to determine the toxic effect of biogenic _nSi before mass production and use of agricultural applications.

This paper considers the evolution of processes applied in agriculture for field operations developed from non-organized handmade activities into very specialized and organized production processes. A set of new approaches based on the application of metaheuristic optimization methods and smart automatization known as Agriculture 4.0 has enabled a rapid increase in in-field operations’ productivity and offered unprecedented economic benefits. The aim of this paper is to review modern approaches to agriculture machinery movement optimization with applications in sugarcane production. Approaches based on algorithms for the division of spatial configuration, route planning or path planning, as well as approaches using cost parameters, e.g., energy, fuel and time consumption, are presented. The combination of algorithmic and economic methodologies including evaluation of the savings and investments and their cost/benefit relation is discussed.

Surface treatment by low-temperature plasma has a great potential in a wide range of applications in many industries and research fields, such as material engineering, automobile industry, ecology, medicine, and agriculture. The application of plasma treatments is relatively new and not very common in agriculture. Protecting cereal seeds against some fungal diseases is one of the plasma applications in agriculture. We tested the possibility of decreased mycotoxin concentration by low pressure and atmospheric pressure plasmas. In addition, we investigated the effects of plasma treatment on nutritive values of the seeds because of their usage as domestic animal feed. The influence on seed germination was also studied and are also reported here.

The control of climatic conditions where cattle are kept is one of the challenges in the livestock sector regarding the digital automation of the process. (1) Background: The main purpose of this study is to define the optimal foundations for automatic climatic systems in organic and energy-sustainable livestock production. In particular, the following components are suggested: (a) the determination of current deviations and interdependency between factors; (b) an algorithm for defining the possible sources of regulation; (c) the ranking approach of the optimal sequence of possible sources; and (d) ensuring transparency and coordination of the model with organic and energy certificates. (2) Methods: This investigation accumulates information on the characteristics of the main microclimatic parameters and simulates their possible combinations in a livestock building in Poland within 24 h of a spring day. A few indices are considered that signal the impact on the thermal comfort of cattle based on the example of recommended measures for the Angus steer genotype. (3) Results: The proposed transparent algorithm is designed for selecting and ranking potential sources of microclimate control according to three criteria. (4) Conclusions: This paper potentially contributes to determining the most optimal digital algorithm for managing microclimate conditions to ensure acceptable comfort for animals, meeting the requirements of organic certification with minimum costs of production, and switching to sustainable types of energy with consideration of technologies’ efficiency. The algorithm is scalable and adjustable to the individual conditions of any livestock premise with a digitally controlled environment.