Predicción del contenido superficial de citral en micropartículas mediante espectroscopía NIR y regresión por mínimos cuadrados parciales
Resumen
En este estudio se evaluó la espectroscopía NIR y la regresión de mínimos cuadrados parciales (PLSR - partial least square regression) en la predicción del contenido superficial de citral (SC- superficial de citral) en micropartículas. Para
este propósito, se prepararon muestras de micropartículas con diferentes niveles de SC variando la relación citral: dextrina (Ct:Dx) en la solución (1:5 y 1:20), y la temperatura del aire de ingreso (TAI) al secador por atomización (120 y 200 °C) durante el secado, obteniendo 12 tratamientos. El contenido SC se midió por cromatografía de gases. Luego, cada tratamiento se dividió en seis partes, cuatro para modelado y dos para validación, obteniendo 72 partes de las cuales su perfil espectral de absorbancia (1100 y 2500 nm), fue extraído y pretratado. Posteriormente, se aplicó el método PLSR para modelar la relación entre los perfiles espectrales y los valores de SC. Se obtuvieron modelos con el espectro completo de onda y modelos optimizados, con las longitudes de onda relevantes. Los resultados obtenidos con el modelo PLSR optimizado mostraron valores de R2 superiores a 0,89 y RMSEC menores de 4,86x10-15. Por tanto; el método NIR – PLSR mostró potencialidades para la determinación de citral en microcápsulas.
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