A review of emerging trends in circular manure management and the role of digital solutions

Abstract

Abstract Livestock manure (LM) management is a crucial aspect of environmental preservation, material sustainability, and sustainable agriculture. However, inadequate LM management can lead to numerous environmental and health issues. To mitigate these negative impacts, improving manure processing conditions through circular manure management (CMM) practices has been widely promoted and implemented. Furthermore, livestock managers are actively utilizing digital technology (DT) and artificial intelligence (AI) to enhance this concept. This is achieved using decision support tools to plan and improve LM collection, storage, emission control, and resource recovery. This study reviews recent technological advancements in CMM practices, the nexus between CMM practices, and the roles of digital solutions. The findings indicate that models, AI, and decision support tools are effectively employed to estimate LM quality parameters. This enables livestock managers to optimize decisions that reduce methane (CH4) and nitrogen oxide (N2O) emissions while controlling ammonia (NH3) emissions on their farms. Technologies such as robotic scrapers and AI-driven collection systems that utilize smart sensors assist in effective LM collection and storage. Additionally, farmers can enhance soil fertility and decrease environmental pollution by fully exploring the nutrient potential in LM. This study examines how LM contributes to material and energy recovery through the creation of bioenergy and organic fertilizers. Despite the significant potential for LM reuse, several obstacles still limit its widespread application within CMM practices, particularly in developing nations. In these regions, the implementation of CMM is hindered by costs, lack of technical expertise, and inadequate infrastructure. Moreover, the widespread adoption of CMM practices is also influenced by geopolitical and economic factors, as observed in countries with inefficient waste management systems. To facilitate sustainable, large-scale CMM practices globally, this study recommends future research areas, including the need for practical, large-scale, cost-effective treatment technologies and the scalability of bioenergy systems in developing nations.