The aim was to establish a rapid and quantitative detection method of formaldehyde in squid based on electronic nose for screening massive samples. Identification of volatile compounds in squid with different formaldehyde content by electronic nose were mainly depended on eight sensors. Besides, the diversities of volatile constituents in squid with increasing contents of aldehydes and aromatic compounds were validated by GC-MS results. Moreover, to build a qualitative discrimination model for estimating whether formaldehyde in squid over standard limit or not, DFA and SIMCA based on PCA were used to analyze electronic nose data for semi-quantitative determination of formaldehyde content in squid. Finally, a rapid quantitative prediction model based on electronic nose and PLS was established (R² = 0.9266).To verify the accuracy of quantitative model, t-test was employed and no significant difference between predicted values and true values was found. This approach showed well potentiality to provide a rapid, nondestructive and quantitative method for detecting formaldehyde residue in food.

目的是建立一种基于电子鼻快速定量检测鱿鱼中甲醛的方法，用于筛查大量样品。通过电子鼻识别不同甲醛含量的鱿鱼中的挥发性化合物主要取决于八个传感器。此外，GC-MS结果验证了鱿鱼中挥发性成分随醛和芳香族化合物含量的增加而变化。此外，为了建立用于评估鱿鱼中甲醛是否超过标准限值的定性判别模型，基于PCA的DFA和SIMCA被用于分析电子鼻数据，以半定量测定鱿鱼中的甲醛含量。最后，建立了基于电子鼻和PLS的快速定量预测模型（R ² = 0.9266）。为验证定量模型的准确性，采用t检验，但预测值与真实值之间没有显着差异。这种方法显示了提供快速，无损和定量的食品中甲醛残留检测方法的潜力。