Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions
Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions
复制标题
高光谱成像与 R 统计和图像处理相结合，用于不同储存条件下日本大香肠 pH 值的检测和可视化
DOI：
10.1111/1750-3841.14024
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发表时间：
2018-02-01
影响因子：
3.9
通讯作者：
Garcia-Martin, Juan Francisco
中科院分区：
文献类型：
--
作者：
Feng, Chao-Hui;Makino, Yoshio;Garcia-Martin, Juan Francisco
使用波长为380至1000 nm的高光谱成像的潜力来确定不同储存条件（4 ℃ 1 d，35 ℃ 1，3和5 d）后熟香肠的pH值。从高光谱图像中提取香肠的平均光谱，并建立偏最小二乘回归（PLSR）模型，将光谱轮廓与熟香肠的pH值联系起来。根据回归系数值选择了11个重要波长。用最佳波长建立的PLSR模型具有较好的预测精度，预测决定系数（R-p（2））为0.909，预测均方根误差为0.035。本文首次用R统计量建立了香肠pH值预测图。实验结果表明，高光谱成像技术结合PLSR和R统计量能够定量和可视化分析不同贮藏条件下香肠的pH值变化。实际应用本文首次将高光谱成像技术应用于R统计量检测熟制香肠的pH值，为没有Matlab软件的研究人员提供了另一种有用的信息。成功地选择了11个最佳波长，用于简化基于全波长建立的PLSR模型。该简化模型具有较高的R-p（2）（0.909）和较低的预测均方根误差（0.035），这对于多光谱成像系统的设计非常有用。
The potential of hyperspectral imaging with wavelengths of 380 to 1000 nm was used to determine the pH of cooked sausages after different storage conditions (4 degrees C for 1 d, 35 degrees C for 1, 3, and 5 d). The mean spectra of the sausages were extracted from the hyperspectral images and partial least squares regression (PLSR) model was developed to relate spectral profiles with the pH of the cooked sausages. Eleven important wavelengths were selected based on the regression coefficient values. The PLSR model established using the optimal wavelengths showed good precision being the prediction coefficient of determination (R-p(2)) 0.909 and the root mean square error of prediction 0.035. The prediction map for illustrating pH indices in sausages was for the first time developed by R statistics. The overall results suggested that hyperspectral imaging combined with PLSR and R statistics are capable to quantify and visualize the sausages pH evolution under different storage conditions.Practical ApplicationIn this paper, hyperspectral imaging is for the first time used to detect pH in cooked sausages using R statistics, which provides another useful information for the researchers who do not have the access to Matlab. Eleven optimal wavelengths were successfully selected, which were used for simplifying the PLSR model established based on the full wavelengths. This simplified model achieved a high R-p(2) (0.909) and a low root mean square error of prediction (0.035), which can be useful for the design of multispectral imaging systems.