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Prediction of meat spectral patterns based on optical properties and concentrations of the major constituents

机译：根据光学特性和主要成分的浓度预测肉的光谱模式

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Abstract A simulation method for approximating spectral signatures of minced meat samples was developed depending on concentrations and optical properties of the major chemical constituents. Minced beef samples of different compositions scanned on a near-infrared spectroscopy and on a hyperspectral imaging system were examined. Chemical composition determined heuristically and optical properties collected from authenticated references were simulated to approximate samples' spectral signatures. In short-wave infrared range, the resulting spectrum equals the sum of the absorption of three individual absorbers, that is, water, protein, and fat. By assuming homogeneous distributions of the main chromophores in the mince samples, the obtained absorption spectra are found to be a linear combination of the absorption spectra of the major chromophores present in the sample. Results revealed that developed models were good enough to derive spectral signatures of minced meat samples with a reasonable level of robustness of a high agreement index value more than 0.90 and ratio of performance to deviation more than 1.4.
机译：摘要根据主要化学成分的浓度和光学性质，开发了一种近似的碎肉样品光谱特征的模拟方法。检查了在近红外光谱仪和高光谱成像系统上扫描的不同组成的牛肉末。试探性地确定化学成分，并模拟从认证参考中收集的光学性质，以近似样品的光谱特征。在短波红外范围内，所得光谱等于三个单独的吸收剂（水，蛋白质和脂肪）的吸收总和。通过假设肉末样品中主要发色团的均匀分布，发现获得的吸收光谱是样品中存在的主要发色团的吸收光谱的线性组合。结果显示，已开发的模型足以导出肉末样品的光谱特征，具有较高的一致性指标值（大于0.90）和性能与偏差比大于1.4的合理鲁棒性。

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