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Detection of Apple Deterioration Using an Electronic Nose and zNosetm

机译:使用电子鼻和zNosetm检测苹果变质

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摘要

Damage in apples can cause fruit spoilage, reduce commodity economic value, and give rise to food quality and safety concerns. This research investigated use of electronic nose (Enose, Cyranose 320) and zNose TM -based nondestructive protocols for rapid detection of deterioration in apples. Key compounds associated with apple aroma were identified using gas chromatography and mass spectrometry, and the differences were observed after 6 days exposure to artificially induced damage in the form of a cut. High-dimensional data were compressed by principal component analysis (PCA) and partial least squares (PLS). Linear discriminant analysis (LDA) and canonical variate analysis (CVA) models were developed based on the compressed data. Experiments showed that both the Enose and zNose were able to effectively detect the volatile differences between undamaged and damaged apples four or more days after the cut. Differences in number of cuts had some effect on volatile compound emissions. Apples subjected to two cuts and three cuts generated volatile profiles that were significantly different from uncut apples. Varying the orientation of cut apples did not give significant differences in the volatile profile. The PLS-LDA model produced the best correct classification rates: 96% using the zNose, and 85% using the Enose
机译:苹果的损坏会导致水果变质,降低商品经济价值,并引起食品质量和安全问题。这项研究调查了使用电子鼻(Enose,Cyranose 320)和基于zNose TM 的无损协议来快速检测苹果变质的情况。使用气相色谱法和质谱法鉴定了与苹果香气有关的关键化合物,在以切口的形式暴露于人工诱导的伤害6天后观察到差异。高维数据通过主成分分析(PCA)和偏最小二乘(PLS)进行压缩。基于压缩数据开发了线性判别分析(LDA)和规范变量分析(CVA)模型。实验表明,Enose和zNose都可以有效地检测切开后四天或更长时间未损坏和受损苹果之间的挥发性差异。削减次数的差异对挥发性化合物的排放有一定影响。经过两次切割和三次切割的苹果产生的挥发性特征与未切割的苹果明显不同。切苹果的方向变化并没有明显改变挥发性成分。 PLS-LDA模型产生了最佳的正确分类率:zNose使用96%,Enose使用85%

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