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Hyperspectral imaging technique for determination of pork freshness attributes

机译：高光谱成像技术确定猪肉的新鲜度

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Freshness of pork is an important quality attribute, which can vary greatly in storage and logistics. The specific objectives of this research were to develop a hyperspectral imaging system to predict pork freshness based on quality attributes such as total volatile basic-nitrogen (TVB-N), pH value and color parameters (L*,a*,b*). Pork samples were packed in seal plastic bags and then stored at 4°C. Every 12 hours. Hyperspectral scattering images were collected from the pork surface at the range of 400 nm to 1100 nm. Two different methods were performed to extract scattering feature spectra from the hyperspectral scattering images. First, the spectral scattering profiles at individual wavelengths were fitted accurately by a three-parameter Lorentzian distribution (LD) function; second, reflectance spectra were extracted from the scattering images. Partial Least Square Regression (PLSR) method was used to establish prediction models to predict pork freshness. The results showed that the PLSR models based on reflectance spectra was better than combinations of LD "parameter spectra" in prediction of TVB-N with a correlation coefficient (r) = 0.90, a standard error of prediction (SEP) = 7.80 mg/100g. Moreover, a prediction model for pork freshness was established by using a combination of TVB-N, pH and color parameters. It could give a good prediction results with r = 0.91 for pork freshness. The research demonstrated that hyperspectral scattering technique is a valid tool for real-time and nondestructive detection of pork freshness.
机译：猪肉的新鲜度是重要的品质属性，在存储和物流中差异很大。这项研究的特定目标是开发一种高光谱成像系统，根据总挥发性碱性氮（TVB-N），pH值和颜色参数（L *，a *，b *）等质量属性来预测猪肉的新鲜度。将猪肉样品包装在密封的塑料袋中，然后在4°C下保存。每12小时。在400 nm至1100 nm的范围内从猪肉表面收集高光谱散射图像。两种不同的方法被用来从高光谱散射图像中提取散射特征谱。首先，通过三参数洛伦兹分布（LD）函数精确拟合各个波长的光谱散射曲线；其次，从散射图像中提取反射光谱。偏最小二乘回归（PLSR）方法用于建立预测模型以预测猪肉的新鲜度。结果表明，基于反射光谱的PLSR模型在预测TVB-N方面优于LD“参数光谱”组合，相关系数（r）= 0.90，标准预测误差（SEP）= 7.80 mg / 100g 。此外，结合TVB-N，pH和颜色参数建立了猪肉新鲜度预测模型。对于猪肉新鲜度，r = 0.91可以给出良好的预测结果。研究表明，高光谱散射技术是实时，无损检测猪肉新鲜度的有效工具。

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