National Engineering Research Center for Optical Instruments, Centre for Optical and Electromagnetic Research, Zhejiang University, Hangzhou 310058, China; Suzhou YouHan Information Technologies, Ltd, Changshu, Suzhou 215500, China.
Mechanical and Electrical Engineering College, Hainan University, Haikou 570228, China.
Meat Sci. 2019 Jun;152:73-80. doi: 10.1016/j.meatsci.2019.02.017. Epub 2019 Feb 23.
It has been demonstrated that optical spectroscopy is a powerful tool for the quantitative monitoring of the main chemical components in food. However, portable spectrometer for on-site food quality assessment has rarely been reported. Here, a low-cost and portable hyperspectral scanner is developed. Utilizing this hyperspectral scanner by handheld push-broom scanning, reflectance spectra of meat samples can be obtained non-invasively and rapidly. Support vector regression (SVR) model is used to predict the pH value. The prediction accuracy rate of the model is close to 90%, and the coefficient of determination is about 0.93, which shows the feasibility of this system in on-site monitoring pH of meat.
已经证明，光学光谱学是定量监测食品中主要化学成分的有力工具。然而，用于现场食品质量评估的便携式光谱仪却很少有报道。在这里，开发了一种低成本、便携式的高光谱扫描仪。利用这种高光谱扫描仪进行手持式推扫扫描，可以快速无创地获得肉样的反射光谱。支持向量回归（SVR）模型用于预测 pH 值。模型的预测准确率接近 90%，决定系数约为 0.93，表明该系统在现场监测肉品 pH 值方面具有可行性。
