Published March 14, 2022 | Version v2

Supplementary files - Evaluation of MALDI-TOF MS technology in small ruminant milk adulteration using raw bovine milk

  • 1. Department of Food Science, Czech University of Life Sciences Prague
  • 2. Department of Computing and Control Engineering, University of Chemistry and Technology
  • 3. Dairy Research Institute Ltd.

Description

The dataset is a part of Supplementary file for the manuscript:

Evaluation of MALDI-TOF MS technology in small ruminant milk adulteration using raw bovine milk by L. Rysova, P. Cejnar, O. Hanus, V. Legarova, J. Havlik, H. Nejeschlebova, I. Nemeckova, R. Jedelska, M. Bozik, submitted to Journal of Dairy Science (Manuscript ID JDS.2021-21396), Received October 8, 2021, Accepted January 31, 2022, Corresponding author: bozik@af.czu.cz, https://doi.org/10.3168/jds.2021-21396

File 1: Detailed MALDI-TOF method description

File 2: Quantification of milk adulteration – calibration of the model Quantification of milk adulteration – calibration of the model

Table S1: Baseline characteristics of pure bovine milk which was used as an adulterant of caprine milk

Table S2: Baseline characteristics of pure bovine milk which was used as an adulterant of ovine milk

Table S3: Root mean squared error (RMSE) of predicted caprine and ovine adulterated milk samples using set A as the training set and set B as the test set.

Table S4: Root mean squared error (RMSE) of predicted caprine and ovine adulterated milk samples using both, set A and set B , as the one training set and set C as the test set.

Table S5: Root mean squared error (RMSE) of predicted caprine and ovine adulterated milk samples using set AB as the training set and set C as the test set.

In this version SD values in Table S2 were corrected.

Notes

The authors thank the Ministry of Agriculture of the Czech Republic (grant NAZV QK1920222 in the program ZEMĚ) for the financial support and METROFOOD-CZ research infrastructure (Prague,Czech Republic; MEYS Grant No: LM2018100) for access to its facilities. P. C. acknowledges support by the Ministry of Education, Youth and Sports of the Czech Republic (Prague, Czech Republic; grant LTAIN19007 Development of Advanced Computational Algorithms for Evaluating Post-surgery Rehabilitation) for data analysis.

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Related works

Is supplement to
Journal article: 10.3168/jds.2021-21396 (DOI)