In this work, a deep analysis of the literature was developed about the causes that promote the low production of methane in the anaerobic digestion (DA) of agro-industrial waste using Data Science, with the aim of discerning the relevance of the scientific developments carried out to address the problems of DA industrial processes in the last five years. Artificial intelligence was used to extract information from 1,003 articles; Subsequently, the distribution and behavior of the information was statistically analyzed using multivariate tools, contrasting data on a laboratory scale and on an industrial scale. It was found that most of the less sophisticated bioreactors - from a technological point of view - are located in developing countries and are used as a waste management strategy and not to generate energy. One third of the waste treated worldwide corresponds to wastewater, the organic fraction of urban solid waste and manure, which is a problem due to the variability and recalcitrant nature of these substrates. Statistically, it was found that there are at least 20 inhibition phenomena in the DA of agro-industrial residues that are widely studied on a laboratory scale, but that are not reported in an equivalent way on an industrial scale, with a marked disparity. The phenomena related to the competition of sulfate reducing bacteria (BSR) and other microbial groups is the main phenomenon reported at the laboratory scale, 30% of the phenomena not addressed correspond to this problem; that is, there is no relevance; which means that the necessary means are not available for their quantification and / or that these problems are not being adequately addressed on industrial level

Inhibition phenomena of anaerobic digestion of agro-industrial waste: data science approach

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