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- Title
基于近红外光谱技术的黄桃脆片可溶性固形物和 硬度定量检测方法.
- Authors
曹念念; 刘 强; 彭 菁; 屠 康; 赵保民; 朱金星; 潘磊庆
- Abstract
The spectrald at a was collected by using two different infrared spectro scopies with 400 to 1 000 nm (visible-shortwave) and 1 000 to 2 500 nm Clongwave) from yellow peach chips. Then four mathematic algorithms, i. e. standard normal variate trans-formation ( SNV), multiplicative scatter correction ( MSC), moving-average smoothing (MS) and 1 st-derivative (1-Der), were utilized in data preprocessing. Regression models by linear partial least square s CPLS) and non-liner support vector machine (SVM) were constructed for the predicting the soluble solids content (SSC) and firmness in yellow peach chips, respectively. Moreover, the feasibility analysis for prediction of SSC and firmness were vittificated by the external experiments. The results showed that the be st performance for SSC prediction was obtained wit h RP of 0.761, RMSEP of 1.998% and RPD of 1.532 by MSC-SVM algorithm in 400 to 1 000 nm. However, the best pedormance for firmness prediction was obtained with RP of 0. 862, RMSEP of 0.292 kg and RPD of 1. 991 by MSC-SVM algorithm in 1 000 to 2 500 nm. All these findings demonstrated that t he near-infrared spectroscopy could be utilized to monitor the quality of fruit chips wit h non-destructive attributes, and also positively promote the development of online automated grading system.
- Publication
Food & Machinery, 2021, Issue 3, p51
- ISSN
1003-5788
- Publication type
Article
- DOI
10.13652/j.issn.1003-5788.2021.03.010