Simply Managing Complex Data

Microbiology

M. Cravero, J. Ruelle, S. Bindschedler, S. Emler, P. Junier. Journal of Food Science, Volume 89, Issue  8, pages 4745-4757.  First published on July 2, 2024.

We’re happy to share a new publication from our collaborators at the Laboratory of Microbiology of the University of Neuchâtel. The article highlights the effectiveness of SmartGene's Centroid-based approach in combating food fraud.

Food fraud is a big challenge in the food industry, and morel mushrooms are no exception. Traditional methods to identify true morels often lack accuracy. Using SmartGene's proprietary, curated reference databases, the authors achieved an impressive 83% accuracy in identifying morel species, compared to just 36% and 47% using traditional tools.

  1. Evaluation of Nucleic Acid Sequencing of the D1/D2 Region of the Large Subunit of the 28S rDNA and the Internal Transcribed Spacer Region Using SmartGene IDNS for Identification of Filamentous Fungi in a Clinical Laboratory
  2. Internal transcribed spacer region sequence analysis using SmartGene IDNS software for the identification of unusual clinical yeast isolates
  3. Systematic Internal Transcribed Spacer Sequence Analysis for Identification of Clinical Mold Isolates in Diagnostic Mycology: a 5-Year Study
  4. DNA Sequencing for the Identification of Unusual Yeasts Encountered in a Clinical Mycology Laboratory