Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics

•Evaluate the quality of jujube fruit samples by NIR spectroscopy and chemometrics•Quantitative analysis of sugar, acid, phenol and antioxidant activity in jujubes•Pattern recognitions were successfully applied for discrimination of jujube fruits.

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of spectra of the jujube (Zizyphus jujuba Mill.) fruit samples from four geographical regions. Prediction models were developed for the quantitative prediction of the contents of jujube fruit, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity. Four pattern recognition methods, principal component analysis (PCA), linear discriminant analysis (LDA), least squares-support vector machines (LS-SVM), and back propagation-artificial neural networks (BP-ANN), were used for the geographical origin classification. Furthermore, three multivariate calibration models based on the standard normal variate (SNV) pretreated NIR spectroscopy, partial least squares (PLS), BP-ANN, and LS-SVM were constructed for quantitative analysis of the four analytes described above. PCA provided a useful qualitative plot of the four types of NIR spectra from the fruit. The LS-SVM model produced best quantitative prediction results. Thus, NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit.

Graphical abstractBy the aid of chemometrics, NIR spectroscopy calibrations were developed for the discrimination of the jujube fruit samples from four geographical regions, and quantitative prediction of their contents, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity, were performed.Figure optionsDownload full-size imageDownload as PowerPoint slide