A systematic literature review on integrated livestock systems using machine learning methods: strengths and future directions from an animal welfare perspective within the "one health" approach

Integrated livestock system (ILS) is a holistic and sustainable farming practice aimed at optimizing the productivity and efficiency of agriculture through the combination of different agricultural components including crops, livestock, aquaculture and forestry. In order to create a balanced ecosystem, reduce waste and increase the efficiency of resource use, as well as contribute to food security, this approach emphasises the interactions between these components. As the ILS has re-emerged due to its potential to maximize production and sustainability, this article provides a systematic literature review on ILS using machine learning. In particular, text mining (TM) and topic analysis (TA) reveal trends, challenges and opportunities in ILS, paving the way for informed decision-making. Descriptive statistics, TM, and TA were carried out on a total of 19 articles retrieved from Scopus (R). The findings revealed an increase in publications in 2023, with TM highlighting the terms that exhibited the highest weighted frequency. Particularly, 'antimicrobial' and 'resist' emerged as the most prominent topics of interest. TA identified the main research areas in the following order: "ILS in aquaculture," "economic models for ILS," "geographical distribution of ILS," "ILS and antimicrobial resistance," and "sustainability in ILS". The analysis suggests that growing awareness of the necessity for sustainable production systems has increased interest in ILS, positioning it as a promising strategy for minimizing environmental impact and increasing resource efficiency.