Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, Korea.
Sensors (Basel). 2013 Sep 30;13(10):13289-300. doi: 10.3390/s131013289.
Spectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400-1,000 nm) spectral range. Moisture measurements were performed using an oven drying method. A partial least squares regression (PLSR) model was developed to extract a relationship between the HSI spectra and the moisture content. In the full wavelength range, the PLSR model possessed a maximum of 0.90 and an SEP of 0.74%. For the NIR range, the PLSR model yielded an of 0.94 and an SEP of 0.71%. The majority of the absorption peaks occurred around 760 and 970 nm, representing the water content in the samples. Finally, PLSR images were constructed to visualize the dehydration and water distribution within different sample regions. The high correlation coefficient and low prediction error from the PLSR analysis validates that HSI is an effective tool for visualizing the chemical properties of meat.
光谱学已被证明是一种测量肉品特性的有效工具。本文采用高光谱成像（HSI）技术，在可见/近红外光谱范围内（400-1000nm）测定煮鸡胸肉的水分含量。采用烘箱干燥法进行水分测量。建立了偏最小二乘回归（PLSR）模型，以提取 HSI 光谱与水分含量之间的关系。在全波长范围内，PLSR 模型的最大值为 0.90，SEP 为 0.74%。对于近红外范围，PLSR 模型的 为 0.94，SEP 为 0.71%。大部分吸收峰出现在 760 和 970nm 左右，代表样品中的水分含量。最后，构建了 PLSR 图像，以可视化不同样品区域内的脱水和水分分布。来自 PLSR 分析的高相关系数和低预测误差验证了 HSI 是可视化肉品化学性质的有效工具。
