Background: There are several methods for the quantification of biomass in SSF, such as glucosamine measurement, ergosterol content, protein concentration, change in dry weight or evolution of CO2 production. However, all have drawbacks when obtaining accurate data on the progress of the SSF due to the dispersion in cell growth on the solid substrate, and the difficulty encountered in separating the biomass. Studying the disadvantages associated with the process of biomass quantification in SSF, the monitoring of the growth of biomass by a technique known as digital image processing (DIP), consists of obtaining information on the production of different compounds during fermentation, using colorimetric methods based on the pixels that are obtained from photographs.
Objective: The purpose of this study was to know about the state of the technology and the advantages of DIP.
Methods: The methodology employed four phases; the first describes the search equations for the SSF and the DIP. A search for patents related to SSF and DIP carried out in the Free Patents Online and Patent inspiration databases. Then there is the selection of the most relevant articles in each of the technologies. As a third step, modifications for obtaining the best adjustments were also carried out. Finally, the analysis of the results was done and the inflection years were determined by means of six mathematical models widely studied.
Results: For these models, the inflection years were 2018 and 2019 for both the SSF and the DIP. Additionally, the main methods for the measurement of biomass in SSF were found, and are also indicated in the review, as DIP measurement processes have already been carried out using the same technology.
Conclusion: In addition, the DIP has shown satisfactory results and could be an interesting alternative for biomass measurement in SSF, due to its ease and versatility.
[http://dx.doi.org/10.1016/j.mib.2005.04.006 PMID: 15939353]
[http://dx.doi.org/10.1007/s10295-008-0309-x PMID: 18228068]
[http://dx.doi.org/10.1016/j.foodchem.2018.11.119 PMID: 30583449]