Visible and Near-Infrared Hyper-Spectral Imaging for the Identification of the Type of Wax on Pears
详细信息 查看全文
- 作者：Baicheng Li ; Yao Zhou ; Mantong Zhao ; Baolu Hou ; Dawei Zhang ; Qi Wang and Yuanshen Huang
- 刊名：Journal of Food Processing and Preservation
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：41
- 期：1
- 全文大小：706K
- ISSN：1745-4549
文摘
This article presents a method for rapid, credible and noninvasive identification of the type of wax on pears using hyper-spectral imaging (HSI) in the visible and near-infrared (Vis–NIR) range (400–1,026 nm). The successive projection algorithm (SPA) was used to select the most effective wavelengths for wax type identification within a calibration set of 108 pears. This set was used to build identification models based on Multiple Linear Regression (MLR) and Linear Discrimination Analysis (LDA) using the relative reflectance values of the effective wavelengths. A prediction set of 72 pears was used to verify the reliability of the models and the results of both models were compared. SPA–LDA was found to be a better model than SPA–MLR, with an identification accuracy of 99.07% for calibration and 95.83% for the prediction sets. This demonstrates that Vis–NIR HSI is a potential candidate for wax type identification in a rapid, credible and noninvasive way.