Fish meal freshness detection by GBDT based on a portable electronic nose system and HS-SPME–GC–MS

Abstract

The volatile compounds of super fresh, superior fresh, general fresh, corrupt and completely corrupt fish meal were studied by headspace solid-phase microextraction–gas chromatography–mass spectrometry. Principal component analysis was used to analyze the sensor and gas chromatography-mass spectrometry data, so as to study the resolution of sensor array. A total of 198 fish meal samples with different freshness were classified by the gradient boosting decision tree method, yielding a model between the sensor array data and the freshness index, such as the acid value and the volatile base nitrogen value. The gradient boosting decision tree model shows that the correlation between the predicted acid value by electronic nose and the measured acid value is 0.90 and the correlation between the predicted volatile base nitrogen value and the measured volatile base nitrogen is 0.97. The combination of an electronic nose and a pattern recognition method based on a gas sensor can predict the acid value and volatile base nitrogen of the freshness index and can detect the freshness of fish meal.