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首页> 外文期刊>Applied Sciences >Fusion of Spectra and Texture Data of Hyperspectral Imaging for the Prediction of the Water-Holding Capacity of Fresh Chicken Breast Filets
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Fusion of Spectra and Texture Data of Hyperspectral Imaging for the Prediction of the Water-Holding Capacity of Fresh Chicken Breast Filets

机译：高光谱成像的光谱和纹理数据融合，用于预测新鲜鸡胸脯肉的保水能力

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摘要

This study investigated the fusion of spectra and texture data of hyperspectral imaging (HSI, 1000–2500 nm) for predicting the water-holding capacity (WHC) of intact, fresh chicken breast filets. Three physical and chemical indicators—drip loss, expressible fluid, and salt-induced water gain—were measured to be different WHC references of chicken meat. Different partial least squares regression (PLSR) models were established with corresponding input variables including the full spectra, key wavelengths, and texture variables, as well as the fusion data of key wavelengths and the corresponding texture variables, respectively. The results demonstrated that for drip loss and expressible fluid, texture data was an effective supplement to spectra data, and fusion data as an input variable could effectively improve the predictive ability of the independent prediction set (Rp = 0.80, RMSEp = 0.80; Rp = 0.56, RMSEp = 2.10). While the best model to predict salt-induced water gain was based on key wavelengths (Rp = 0.69, RMSEp = 18.04), this was mainly because salt-induced water gain was measured on mince samples, which lacked the important physical structure to represent the texture information of meat. Our results of this study demonstrated the potential to further improve the evaluation of the WHC of chicken meat by HSI.
机译：这项研究调查了高光谱成像（HSI，1000-2500 nm）的光谱和纹理数据的融合，以预测完整，新鲜的鸡胸脯肉的持水量（WHC）。三种物理和化学指标（滴水损失，可表达的液体和盐分引起的水分增加）被测量为鸡肉的WHC参考值不同。使用相应的输入变量（包括全光谱，关键波长和纹理变量，以及关键波长的融合数据和相应的纹理变量）建立了不同的偏最小二乘回归（PLSR）模型。结果表明，对于滴落损失和可表达的流体，纹理数据是光谱数据的有效补充，融合数据作为输入变量可以有效提高独立预测集的预测能力（Rp = 0.80，RMSEp = 0.80; Rp = 0.56，RMSEp = 2.10）。预测盐分引起的水分增加的最佳模型是基于关键波长（Rp = 0.69，RMSEp = 18.04），这主要是因为在肉末样品上测量了盐分引起的水分增加，而盐分缺乏重要的物理结构来表示盐分。肉的质地信息。我们的这项研究结果表明，通过HSI可以进一步改善对鸡肉WHC的评估。

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