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The aim of this study was to develop and validate a community supported online infrastructure and bioresource for methane yield data and accompanying metadata collected from published literature. In total, 1164 entries described by 15,749 data points were assembled. Analysis of data collection showed little congruence in reporting of methodological approaches. The largest identifiable source of variation in reported methane yields was represented by authorship (i.e. substrate batches within particular substrate class) within which experimental scales (volumes (0.02-5l), incubation temperature (34-40 °C) and % VS of substrate played an important role (p < 0.05, npermutations = 999) as well. The largest fraction of variability, however, remained unaccounted for and thus unexplained (> 63%). This calls for reconsideration of accepted approaches to reporting data in currently published literature to increase capacity to service industrial decision making to a greater extent., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The primary aim of the study was to develop and validate an in-house upscale of Automatic Methane Potential Test System II for studying real-time inocula and real-scale substrates in batch, codigestion and enzyme enhanced hydrolysis experiments, in addition to semi-continuous operation of the developed equipment and experiments testing inoculum functional quality. The successful upscale to 5L enabled comparison of different process configurations in shorter preparation times with acceptable accuracy and high-through put intended for industrial decision making. The adoption of the same scales, equipment and methodologies in batch and semi-continuous tests mirroring those at full scale biogas plants resulted in matching methane yields between the two laboratory tests and full-scale, confirming thus the increased decision making value of the approach for industrial operations., (Copyright © 2013 Elsevier Ltd. All rights reserved.)