Detection of apple deterioration using an electronic nose and zNose™

Damage in apples can cause fruit spoilage, reduce commodity economic value, and give rise to food quality and safely concerns. This research investigated use of electronic nose (Enose, Cyranose 320) and zNose™ -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.