Myoglobin-Based Classification of Minced Meat Using Hyperspectral Imaging

• Main Authors: Hamail Ayaz, Muhammad Ahmad, Ahmed Sohaib, Muhammad Naveed Yasir, Martha A. Zaidan, Mohsin Ali, Muhammad Hussain Khan, Zainab Saleem
• Format: Article
• Language: English
• Published: MDPI AG 2020-09-01
• Series: Applied Sciences
• Subjects: hyperspectral imaging; myoglobin (Mb) spectral features; <i>isos-bestic</i> points; substitution; Bovine (beef); Ovine (mutton)
• Online Access: https://www.mdpi.com/2076-3417/10/19/6862

Minced meat substitution is one of the most common frauds which not only affects consumer health but impacts their lifestyles and religious customs as well. A number of methods have been proposed to overcome these frauds; however, these mostly rely on laboratory measures and are often subject to human error. Therefore, this study proposes novel hyperspectral imaging (400–1000 nm) based non-destructive <i>isos-bestic</i> myoglobin (Mb) spectral features for minced meat classification. A total of 60 minced meat spectral cubes were pre-processed using true-color image formulation to extract regions of interest, which were further normalized using the Savitzky–Golay filtering technique. The proposed pipeline outperformed several state-of-the-art methods by achieving an average accuracy of <inline-formula><math display="inline"><semantics><mrow><mn>88.88</mn><mo>%</mo></mrow></semantics></math></inline-formula>.