Due to the success of Microbiome and Machine Learning, which collected research results and perspectives of researchers working in the field of machine learning (ML) applied to the analysis of microbiome data, we are launching the second volume to collate any new findings in the field to further our understanding and encourage the participation of experts worldwide in the discussion. The success of ML algorithms in the field is substantially due to their capacity to process high-dimensional data and deal with uncertainty and noise. However, to maximize the combinatory potential of these emerging fields (microbiome and ML), researchers have to deal with some aspects that are complex and inherently related to microbiome data. Microbiome data are convoluted, noisy and highly variable, and non-standard analytical methodologies are required to unlock their clinical and scientific potential. Therefore, although a wide range of statistical modelling and ML methods are available, their application is only sometimes optimal when dealing with microbiome data.

This is Volume II of the Research Topic "Interactions between Bioactive Food Ingredients and Intestinal Microbiota". The previous edition can be found here. Numerous microorganisms colonize the gastrointestinal tract playing critical roles concerning digestion and absorption of dietary nutrients and the regulation of important functions, including host metabolism, immunity, and intestinal barrier function. Increasing evidence suggests that food encompassing nutrients and polyphenols are strong drivers shaping the composition and function of the gut microbiota and mediate the host's physiological activities directly or indirectly. However, the mechanisms involved in the interactions between food nutrients/prebiotics, gut microbiota and host health have not been enlightened to a wide extent.

The use of biocontrol agents and beneficial organisms for management of plant and pest diseases appears as an environment-friendly and economic procedure. However, this option is not always available, depending on the lack of knowledge on the mechanisms of natural regulation, locally effective. In this view, this eBook considers studies and experimental works illustrating a range of problems and solutions based on microbial resources, suitable for management of biotic stress factors. These examples show how detailed data and knowledge on the organisms involved are of paramount importance to achieve a sustainable and durable management capability.