Abstract
In this paper, ridgetail white prawn (Exopalaemon carinicauda) K value predicting model by electronic nose (EN) was studied. Human sensory evaluation (HSE), weight loss, color, total viable counts (TVC), GC-MS, and K value were examined to provide quality references for EN detection. EN responses to prawns were recorded and processed by principal component analysis (PCA) and stochastic resonance (SR). Results indicated that prawn K value rapidly increased due to microbiology propagation. The volatile gases emitted by prawns increased with the increase of storage time based on GC-MS results. PCA method could not discriminate the prawns in different qualities, and SR signal-to-noise ratio (SNR) maximum (SNRmax) values successfully discriminated all samples. K value predicting model was developed by linear fitting regression between K values and SNRmaxvalues (R2 = 0.97). The proposed method will promote the applications of EN in aquatic product quality rapid determination.
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