Developing and Implementing an R Shiny Application to Introduce Multivariate Calibration to Advanced Undergraduate Students
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Tomás M. Antonelli [1] ; Alejandro C. Olivieri [1]
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[1] Universidad Nacional de Rosario
Universidad Nacional de Rosario
Argentina
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- Localización: Journal of chemical education, ISSN 0021-9584, Vol. 97, Nº 4, 2020, págs. 1176-1180
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
During a short chemometrics course in the seventh semester of the chemistry undergraduate program, students receive a brief theoretical introduction to multivariate calibration, focused on partial least-squares regression as the most commonly employed data processing tool. The theory is complemented with the use of MVC1_R, an easy-to-use software developed in-house as an R Shiny application. The present report describes student activities with the latter software in the development of mathematical models to predict quality parameters of corn seeds from near-infrared spectra. Subsequently, an experimental project is carried out involving near-infrared spectral measurements, which are widely used in several industrial fields for quality control. To process the obtained data, students apply the knowledge acquired during the theoretical/software sessions.
