Rapid evaluation of chicken meat freshness using gas sensor array and signal analysis considering total volatile basic nitrogen

• Main Authors: Xuxiang Tang, Zhi Yu
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2020-01-01
• Series: International Journal of Food Properties
• Subjects: chicken meat; total volatile basic nitrogen; rapid prediction; gas sensor array; stochastic resonance
• Online Access: http://dx.doi.org/10.1080/10942912.2020.1716797

Total volatile basic nitrogen (TVB-N) level rapid evaluation on chicken meat based on gas sensor array (GSA) technique was studied in this paper. GSA responses to chicken meat stored at 4°C were examined for 5 days. TVB-N content was synchronously measured by chemical examination. Principal component analysis (PCA) and non-linear double-layered cascaded serial stochastic resonance (DCSSR) were utilized for measurement data analysis. TVB-N examination results suggested that chicken meat stored for more than 3 days was not fresh. PCA showed poor discrimination abilities, while DCSSR signal-to-noise ratio (SNR) quantitatively characterized the freshness of all samples. Chicken meat TVB-N forecasting model was developed by non-linear fitting between SNR eigenvalues and TVB-N values. The predicting model was constructed. Validation experiment results demonstrated that the forecasting accuracy of the developed model reached 93.3%.