[Discrimination of brownheart and watercore of apples based on energy spectrum of visible/near infrared transmittance].
It is urgent to develop a quick and precise method for the discrimination of the internal quality of apple. Vis/NIR spectroscopy combined with multivariate analysis after the appropriate spectral data pre-treatment has been proved to be a very powerful tool for judgment of objects that have very similar exterior properties. In the present study, peak area discriminant analysis (PADA), principal component analysis discriminant analysis (PCADA) and partial least squares discriminant analysis (PLSDA) were applied to classify apples with different internal properties such as brownherat and watercore. Energy spectra were processed using MSC or one-order derivative, and three models using PADA, PCADA and PLSDA were built, respectively. The accuracy rates of prediction for brownheart apple were 100%, for watercore apple were 79.6%, 95.0% and 96.7%, and for natural apple were 88.4%, 98.2% and 98.8%, respectively. The PLSDA model was better than the others remarkably. And the overall correct ratio of PLSDA was 98.1%, with RMSEC = 0.449 and RMSEP = 0.392. The results in the present study show that Vis/NIR spectroscopy together with chemometrics techniques could be used to differentiate brownheart and watercore apple, which offers the benefit of avoiding time-consuming, costly and sensory analysis.
Wang
Jia-hua
JH
College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China. w.jiahua@163.com
Sun
Xu-dong
XD
Pan
Lu
L
Sun
Qian
Q
Han
Dong-hai
DH
D000465:Algorithms; D016002:Discriminant Analysis; D005506:Food Contamination / Q000032:analysis*; D016018:Least-Squares Analysis; D027845:Malus / Q000737:chemistry*; D025341:Principal Component Analysis / Q000379:methods; D019265:Spectroscopy, Near-Infrared