Texture Analysis of Corn-based Snacks with Fast Fourier Transform Artículo académico uri icon

Abstracto

  • This paper introduces a computer-based system devoted to process the sound that is produced when a corn-based food product is masticated. The system allows a simple and high-quality sound acquisition eliminating any interference caused by noise and other environmental artifacts. Its user interface displays the collected data in both time and frequency domains. Using the Fast Fourier Transform (FFT), some of the main characteristics related to food texture can be determined. The proposed implementation intends to be a simple yet effective tool that could complement sensory analysis in the food industry by assisting in determining the crunchiness of corn-based snacks, which is often a desirable attribute by consumers.

fecha de publicación

  • 2022

Publicado en

Palabras clave

  • Corn-based snacks
  • Fast Fourier Transform
  • Food texture
  • Sensory analysis
  • Sound processing

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