The problems arising from the limited availability of natural resources and the impact of certain anthropogenic activities on the environment must be addressed as soon as possible. To meet this challenge, it is necessary, among other things, to reconsider and redesign agricultural systems to find more sustainable and environmentally friendly solutions, paying specific attention to waste from agriculture. Indeed, the transition to a more sustainable and circular economy should also involve the effective valorization of agricultural waste, which should be seen as an excellent opportunity to obtain valuable materials. For the reasons mentioned above, this review reports and discusses updated studies dealing with the valorization of agricultural waste, through its conversion into materials to be applied to crops and soil. In particular, this review highlights the opportunity to obtain plant biostimulants, biofertilizers, and biopolymers from agricultural waste. This approach can decrease the impact of waste on the environment, allow the replacement and reduction in the use of synthetic compounds in agriculture, and facilitate the transition to a sustainable circular economy.
Biogas-based energy production has become a successful strategy for many livestock farms around the world. However, raw materials production is threatened by a growing uncertainty due to effects of climate change on crops cultivation. The aim of this paper is to propose a tool for the optimal design of the biogas mixture, considering respectively the nutritional needs of livestock and the parameters of the biogas process. Within a context of climate variability, a three-stage Discrete Stochastic Programming (DSP) model is applied in a dairy cattle farm with anaerobic digestion plant. This state-contingent approach (DSP model) considers, as uncertain parameters, the watering needs and the yields of forage and energetic crops. The DSP model is compared with equivalent models of expected values to verify the benefits derived from the explicit inclusion of climatic states. The results showed a remarkable improvement in the efficiency of feedstock management, reflecting in a significant reduction in farm costs (11.75 %) compared to the baseline scenario. Whereas, the comparison between the state-contingent approach and the expected value model, showed only slight benefits (0.02 %). This confirms that the DSP model’s ability to offer a better hedged solution increases when high climate variability affects crop yields and irrigation needs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.