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A nondestructive detection method of multi-quality parameters of beef by visible/near-infrared spectroscopy

机译:可见光/近红外光谱法的牛肉多质量参数的非破坏性检测方法

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The water content, color and pH value of beef play important roles in the evaluation of beef quality. The traditional determination methods of these parameters are destructive and time-consuming while a lot of literature show that visible and near-infrared spectrum have great potential in the determination of beef quality. In this paper, a method was developed to determine the water content, color and pH value of beef simultaneously. A detection probe with ring illuminator was built to improve the performance of the instrument. Sixty pieces of beef were collected from the supermarkets and famers markets of Beijing, while 75% of the samples were used as the calibration set of the model, the rest of the samples were used as the validation set. The reflectancespectra data of the samples werecollected by a dual channel visible and near infrared spectroscopic system in the range of 400nm to 2600nm, which the first section with a range of 400nm to 950nm and the second section with a range of 800nm to 2600nm. The diffuse reflectance spectrum of samples was performed with different pretreatments, such as standard normal variable transformation (SNV), detrend (DE) and multiplication scatter correction (MSC). Partial least squares regression (PLSR) models were establishedfor prediction of all these four parameters, respectively. Correlation coefficient (R) and root mean square error (RMSE) between prediction data and real data of the samples were used as evaluation criterions for the prediction model. Thespectral data of the first channel, the second channel and the full spectrum were conducted with the same pretreatment methods and modeling methods respectively. The results show that the utilization of the new detection probe achieved an effective improvement of the correlation coefficients and stability compared with the previous probes, and the PLSR models performed pretty well with better predicted correlation coefficient (R>0.85) and relatively small root mean square error. The present method builtby visible and near-infrared spectroscopy based on the new detection probe with ring illuminator can detect water content, color and pH value of beef nondestructively and rapidly.
机译:牛肉的水含量,颜色和pH值在牛肉质量评估中起重要作用。这些参数的传统测定方法是破坏性和耗时的,而很多文献表明可见的和近红外光谱在牛肉质量的测定中具有很大的潜力。在本文中,开发了一种方法以同时测定牛肉的水含量,颜色和pH值。建立了带环形照明器的检测探头,以提高仪器的性能。从超市和北京的名额收集六十件牛肉,而75%的样品被用作模型的校准组,其余的样品用作验证集。样品的反射议程数据通过双通道可见和近红外光谱系统的射程,其范围为400nm至2600nm,该第一部分的范围为400nm至950nm,第二部分为800nm至2600nm。样品的漫反射谱谱谱用不同的预处理进行,例如标准正常可变变换(SNV),DEDREND(DE)和乘法散射校正(MSC)。部分最小二乘回归(PLSR)模型分别建立了所有这四个参数的预测。预测数据与样本的真实数据之间的相关系数(R)和均方根误差(RMSE)用作预测模型的评估标准。用相同的预处理方法和建模方法进行第一通道,第二通道和全谱的传感数据。结果表明,与先前的探测器相比,新检测探针的利用率实现了相关系数和稳定性的有效改善,并且PLSR模型具有更好的预测相关系数(R> 0.85)和相对较小的根均方错误。本方法基于具有环形照明器的新检测探针的可见和近红外光谱的方法可以无损且迅速地检测牛肉的水含量,颜色和pH值。

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