Prediction of Texture of Raw Poultry Meat by Visible and Near–Infrared Reflectance Spetroscopy

Authors

  • Herlina Abdul Rahim Process Tomography and Instrumentation Engineering Research Group (PROTOM-i), Infocomm Research Alliance, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Rashidah Ghazali Process Tomography and Instrumentation Engineering Research Group (PROTOM-i), Infocomm Research Alliance, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Shafishuhaza Sahlan Process Tomography and Instrumentation Engineering Research Group (PROTOM-i), Infocomm Research Alliance, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Mashitah Shikh Maidin Faculty of Biology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia

DOI:

https://doi.org/10.11113/jt.v64.2133

Keywords:

Chicken meat, tenderness, NIRS, Volodkevich Bite Jaws, partial least squares

Abstract

Near-infrared (NIR) spectroscopy is a non-destructive, low cost and fast measurement technique that is required to improve the meat texture quality prediction. In this research, visible/NIR spectroscopy has been used for the prediction of raw chicken meat texture from different types of chickens by referring to the reference data obtained from destructive measurement using a Volodkevich Bite Jaws texture analyser. The Partial Least Squares analysis shows that the prediction accuracy is higher for the Az-Zain village organic chickens (85–95%) than for village chickens (42–68%) and broiler chickens (42–44%). The high prediction accuracy and low absorbance spectra of Az-Zain village organic chickens compared to broiler and village chickens could be correlated with the food composition of the chicken meal.

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Published

2013-09-15

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Section

Science and Engineering

How to Cite

Prediction of Texture of Raw Poultry Meat by Visible and Near–Infrared Reflectance Spetroscopy. (2013). Jurnal Teknologi, 64(5). https://doi.org/10.11113/jt.v64.2133