Grape Cultivar Identification and Classification by Machine Olfaction Analysis of Leaf Volatiles

Development of electronic technologies for precise identification fruit crop cultivars in agricultural production provides an effective means assuring product quality and authentication. The capabilities discriminating between grape (Vitis vinifera L.) is essential certification varieties sold world markets. Machine olfaction, based on electronic-nose (e-nose) technologies, readily available rapid vegetative products. This technology relies detection discrimination volatile organic compound (VOC) emissions from plant parts. It may be used all stages to facilitate maintenance, cultivation, harvesting decisions prior marketing. An experimental e-nose device was constructed tested combination with five chemometric methods, including PCA, LDA, QDA, SVM, ANN, as rapid, non-destructive tools classification cultivars. instrument equipped nine metal oxide semiconductor (MOS) sensors utilized identify classify leaf VOC using supervised non-supervised methods. Grape samples were first identified belonging specific cultivar types PCA analyses, which are the two principal components (PC-1 PC-2) accounting 89% total variance. Four statistical methods further tested, DA, provided accuracies 98%, 99%, 92%, respectively. These findings confirmed suitable applicability MOS sensor array accurate cultivars, useful authentication vine commercial