|Table of Contents|

Identification of Apple Varieties Based on Spectroscopy Technology Combined With Chemometrics

《北方园艺》[ISSN:1001-0009/CN:23-1247/S]

Issue:
2019年16
Page:
66-71
Research Field:
Publishing date:

Info

Title:
Identification of Apple Varieties Based on Spectroscopy Technology Combined With Chemometrics
Author(s):
SHANG Jing1; 2; ZHANG Yan2; MENG Qinglong1; 2
(1.Food and Pharmaceutical Engineering Institute，Guiyang University，Guiyang，Guizhou 550005；2.The Research Center of Nondestructive Testing for Agricultural Products，Guiyang University，Guiyang，Guizhou 550005)
Keywords:
ultravioletradiation/visible spectroscopy; chemometrics; principal component analysis; nondestructive identification
PACS:
-
DOI:
10.11937/bfyy.20183895
Abstract:
The recognition models of three different apple varieties (‘Candy’‘Gala’ and ‘Fuji’ apple) were established based on UV/VIS spectroscopy technology combined with K nearest neighbor (KNN) and partial least-square discriminant analysis (PLS-DA)，respectively.Then the influence of the different spectrum pretreatment methods (second derivation (SD)，standard normal variation (SNV) and multi-scatter calibration (MSC)) on the recognition models was analyzed.Finally，the characteristic spectrum of apples were extracted by the principal component analysis.The results showed that the first six principal components with the cumulative contribution rate above 99% were selected as the characteristic spectral data in the sample set by the principal component analysis，and the dimensionality reduction of the spectral data was well achieved.The effect of second derivation preprocessing for the spectrum data was the best.In conclusion，the recognition models all had an acceptable accuracy，especially SD+KNN model had optimal recognition performance for modeling set and MSC+KNN model had optimal recognition performance for prediction set.And SD+PLS-DA model had optimal total recognition performance.

References:

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Last Update: 2019-08-29