Abstract
Spectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400–1,000 nm) spectral range. Moisture measurements were performed using an oven drying method. A partial least squares regression (PLSR) model was developed to extract a relationship between the HSI spectra and the moisture content. In the full wavelength range, the PLSR model possessed a maximum R2p of 0.90 and an SEP of 0.74%. For the NIR range, the PLSR model yielded an R2p of 0.94 and an SEP of 0.71%. The majority of the absorption peaks occurred around 760 and 970 nm, representing the water content in the samples. Finally, PLSR images were constructed to visualize the dehydration and water distribution within different sample regions. The high correlation coefficient and low prediction error from the PLSR analysis validates that HSI is an effective tool for visualizing the chemical properties of meat.
Highlights
Chicken meat is preferred across the World due to its high nutrient value and flavor.Consumers continually demand high meat quality
(b) Develop a partial least squares regression (PLSR) model to analyze the spectral data among the measured moisture values and identify the effective wavelength related to the meat water content. (c) Develop image processing algorithms for the visualization of chemical images of the moisture at three different temperature variations
We estimated the correct number of latent variables (LV) using the root mean square error (RMSE) method and the performance of the PLSR model reported as the acquired accuracy of R2
Summary
Chicken meat is preferred across the World due to its high nutrient value (protein content) and flavor. A change in these properties influences juiciness, texture, fat composition, water content (moisture), size and other properties These properties generally change during different processing techniques such as thawing, chilling, marinating, handling and cooking. Hyperspectral imaging (HSI) is a three-dimensional technique, consisting of both images and spectra, which yields physical and chemical information These hyperspectral techniques are the best potential tool for measuring the water content and distribution in the. This information cannot be obtained using any other conventional technique For this reason, we apply hyperspectral imaging techniques to determine the moisture content in cooked chicken breast meat with the following objectives: (a) Establish a visual/near infrared (VIS/NIR) hyperspectral imaging system (400–1,000 nm) for obtaining spectrum of the cooked chicken breast samples. (b) Develop a PLSR model to analyze the spectral data among the measured moisture values and identify the effective wavelength related to the meat water content. (c) Develop image processing algorithms for the visualization of chemical images of the moisture at three different temperature variations
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