Video Experimental Relacionado

Updated: Jan 24, 2026

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Espectroscopía ATR-FTIR y aprendizaje profundo para análisis quimiométrico y clasificación geográfica de vinos tintos

Shengwei Wang¹, Keda Chen¹, Yize Wang¹

¹School of Computer Science and Engineering, Northwest Normal University, Lanzhou, China.

Journal of food science

|January 23, 2026

Resumen

Este estudio utiliza espectroscopía infrarroja y un novedoso modelo de IA para autenticar los orígenes del vino tinto. El método identifica con precisión las diferencias regionales en la composición química del vino, garantizando una trazabilidad geográfica fiable.

Conclusiones:

La combinación de la espectroscopía ATR-FTIR y el modelo Res-MCNN proporciona un método altamente eficaz y fiable para la autenticación del origen geográfico del vino tinto.
El modelo desarrollado demuestra un rendimiento sólido en la identificación de características espectrales regionales, lo que contribuye a la autenticidad y trazabilidad del vino.
Este enfoque ofrece una herramienta prometedora para la industria del vino para combatir el fraude y garantizar la procedencia del producto.

Palabras clave:

Espectroscopía infrarroja de transformada de Fourier reflexión total atenuada análisis quimiométrico aprendizaje profundo clasificación geográfica características espectrales de alta dimensión

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