Estimación de la composición química de granos y pastas proteicas mediante espectroscopia (NIRS-FTIR)
DOI:
https://doi.org/10.22319/rmcp.v16i2.6637Palabras clave:
Espectroscopía, Alimentos, CerdosResumen
El objetivo de este estudio fue utilizar la espectroscopía de reflectancia del infrarrojo cercano (NIRS) para estimar la composición química de ingredientes para cerdos. Se recolectaron muestras (n=118) de granos (maíz y sorgo) y harinas (soya y canola). Las muestras se analizaron para materia seca (MS), materia orgánica (MO), proteína cruda (PB), extracto etéreo (EE), fibra detergente neutro (FDN) o fibra detergente ácido (FDA), almidón total (almidón y energía bruta (EB) y fueron escaneadas con un espectrofotómetro FTIR. Con esta información, ecuaciones de calibración (ECS) fueron desarrolladas con el uso de un paquete de programa (TQ Analyst; Thermo Fisher Scientific). La selección de CE se basó en la minimización de los errores estándar de calibración (EEC), de la validación cruzada (EEVC) y de predicción (EEP), y la maximización de los coeficientes de determinación de la calibración (R2cal), y validación. (R2val). El poder predictivo de la ECS se evaluó mediante la estadística RPD (tasa/desviación de predicción). Excepto MS, las estadísticas de MO (0,99, 0,21, 0,39, 0,999, 0,34 y 7,3), PC (0,99, 0,62, 0,95, 0,998; 0,99 y 28,2), EE (0,98, 0,15, 0,31, 0,963, 0,22 y 3,7), FDN (0,98, 0,60, 1,82, 0,962; 1,38 y 3,6), ADF (0,99, 0,70, 1,43, 0,979, 1,04 y 4,6), almidón (0,99, 2,31, 3,34, 0,994; 3,03 y 9.7) y EB (0.98, 22.8, 34.9, 0.976; 36.0 y 4.2), R2cal, EE, EEVC, R2val, EEP y RPD, respectivamente, apoyan la conclusión de que los ECS tienen una capacidad predictiva aceptable de la composición química de ingredientes para la alimentación de cerdos.
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