{
  "annotation_id": "00ac92cf-2e72-45cc-81ba-907609be5080",
  "date_created": "2026-03-02T18:01:34.684000Z",
  "date_modified": "2026-03-02T18:01:34.684000Z",
  "file_hash": "8d0322df88b52fc19259e636220198a936a88ec4c4572f76e87d924352f5b634",
  "private": false,
  "record": {
    "abstract": "We present an algorithm for the continuous monitoring of the biomass and\nethanol concentrations and moreover the kinetic rate in the Mezcal fermentation\nprocess. This algorithm performs its task having only available the on-line\nmeasurements of the redox potential. The procedure includes an artificial\nneural network (ANN) that relates the redox potential to the ethanol and\nbiomass concentrations. Then a nonlinear-observer-based algorithm uses the\nbiomass estimations to infer the kinetic rate of this fermentation process. The\nmethod shows that the redox potential is a valuable indicator of microorganism\nmetabolic activity during the Mezcal fermentation. In addition, the estimated\nkinetic rate can be considered as a direct evidence of the presence of mixed\nculture growth in the process. In this work, the detailed design of the\nsoftware-sensor is presented, as well as its experimental application at the\nlaboratory level",
    "arxiv_id": "q-bio/0609049",
    "authors": [
      "P. Escalante-Minakata",
      "V. Ibarra-Junquera",
      "H. C. Rosu",
      "A. De Leon-Rodriguez",
      "R. Gonzalez-Garcia"
    ],
    "categories": [
      "q-bio.QM"
    ],
    "title": "An algorithm for real-time estimation of Mezcal fermentation parameters   based on redox potential measurements",
    "url": "https://arxiv.org/abs/q-bio/0609049"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e8e21be7-d900-4183-814d-a81e6d406f07",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}