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Food Analytical Methods

, Volume 13, Issue 1, pp 260–267 | Cite as

Development of an Automated Analytical System of Low Cost for High-Throughput Infrared Thermometric Titration

  • Iberê Damé Teixeira
  • Bruna Tischer
  • Roberta Oliveira Santos
  • Keiti Oliveira Alessio
  • Gilson Augusto Helfer
  • Liane Mahlmann Kipper
  • Juliano Smanioto Barin
  • Adilson Ben da CostaEmail author
Article
  • 108 Downloads

Abstract

Thermometric titration is an enthalpimetric technique of analysis that uses the enthalpy variation of a reaction to determine the equivalence point of a titration for quantification of the analyte. One of the advantages of this technique is that it does not require sample preparation, such as digestion; it only needs to weigh the sample and add auxiliary reagents. Based on this technique, the aim of this work was to develop automated equipment for thermometric titration, using a contactless infrared temperature sensor. The equipment was manufactured using the concept of additive manufacturing. A Raspberry Pi microcomputer was used to interpret the signal from the temperature sensor and to control a micropump used to dispense titrant at a rate selected by the user. Components were designed using computer-aided design (CAD) software and printed on a fused deposition material printer. For evaluation of the equipment, tests were performed using neutralization and precipitation reactions, measuring the total acidity of vinegars and sodium in sauces. The temperature of reaction was plotted in an enthalpogram, from which the endpoint could be determined. Values of agreement between the method proposed and the reference method ranged from 100 to 104% for total acidity of vinegars and from 96 to 105% for the determination of sodium in sauce. The equipment proved to be technically feasible and of low cost, given that it used alternative and biodegradable materials such as polylactic acid.

Keywords

Thermometric titration Infrared enthalpimetry Direct sodium determination Total acidity 

Notes

Funding Information

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS).

Compliance with Ethical Standards

Conflict of Interest

Iberê Damé Teixeira declares no conflict of interest. Bruna Tischer declares no conflict of interest. Roberta Oliveira Santos declares no conflict of interest. Keiti Oliveira Alessio declares no conflict of interest. Gilson Augusto Helfer declares no conflict of interest. Liane Mahlmann Kipper declares no conflict of interest. Juliano Smanioto Barin declares no conflict of interest. Adilson Ben da Costa declares no conflict of interest.

Ethical Approval

This article does not contain any studies with human or animal subjects.

Informed Consent

Publication has been approved by all individual participants.

Supplementary material

12161_2019_1613_MOESM1_ESM.docx (991 kb)
ESM 1 (DOCX 990 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Iberê Damé Teixeira
    • 1
  • Bruna Tischer
    • 2
  • Roberta Oliveira Santos
    • 1
  • Keiti Oliveira Alessio
    • 3
  • Gilson Augusto Helfer
    • 4
  • Liane Mahlmann Kipper
    • 1
  • Juliano Smanioto Barin
    • 3
  • Adilson Ben da Costa
    • 1
    Email author
  1. 1.Programa de Pós-Graduação em Sistemas e Processos IndustriaisUniversidade de Santa Cruz do SulSanta Cruz do SulBrazil
  2. 2.Instituto de Ciência e Tecnologia de AlimentosUniversidade Federal do Rio Grande do SulPorto AlegreBrazil
  3. 3.Departamento de Tecnologia e Ciência dos AlimentosUniversidade Federal de Santa MariaSanta MariaBrazil
  4. 4.Programa de Pós-Graduação em Computação AplicadaUniversidade Vale do Rio dos SinosSão LeopoldoBrazil

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