title: Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics.
abstract: 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.
authors: College of Chemistry, Nanchang University, Nanchang 330031, China.
authors: Ying
authors: Y
authors: Guo
authors: College of Chemistry, Nanchang University, Nanchang 330031, China; State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China. Electronic address: ynni@ncu.edu.cn.
authors: Yongnian
authors: Y
authors: Ni
authors: School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, QLD University of Technology, Brisbane 4001, Australia. Electronic address: s.kokot@qut.edu.au.
authors: Serge
authors: S
authors: Kokot
mesh_terms: D000143:Acids / Q000032:analysis; D000975:Antioxidants / Q000032:analysis; D002138:Calibration; D002241:Carbohydrates / Q000032:analysis; D016002:Discriminant Analysis; D005638:Fruit / Q000737:chemistry*; D016018:Least-Squares Analysis; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D010636:Phenols / Q000032:analysis; D025341:Principal Component Analysis; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D060388:Support Vector Machine; D031957:Ziziphus / Q000737:chemistry*
chemical_list: D000143:Acids; D000975:Antioxidants; D002241:Carbohydrates; D010636:Phenols
keywords: Antioxidant activity; Chemometrics; Jujube (Zizyphus jujuba Mill.) fruit; Near-infrared spectroscopy; Phenol content; Sugar; Total acid