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Use of signal to noise ratio and area change rate of spectra to evaluate the Visible/NIR spectral system for fruit internal quality detection

机译:使用信噪比和光谱的面积变化率评估可见/近红外光谱系统以检测水果内部质量

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The stability of a spectroscopic measuring system is very important in non-destructive internal quality measurement of agriculture products by Visible and NIR (Vis/NIR) spectroscopy at factory level. However, few works have been published about how to evaluate whether or not the spectroscopic measuring system is reasonable. In this paper, signal to noise ratio (SNR) and area change rate (ACR) of the spectra of reference standard were used to evaluate the Vis/NIR spectral system. Two different systems with different light sources (LSI and LS2) were considered. The results showed that the SNR recorded at each selected wavelength in the condition of LSI was higher than that recorded in the condition of LS2, and the ACR between 550 nm and 920 nm in the condition of LS1 was smaller than that of LS2. Meanwhile, in the verification experiment by calibration and cross-validation analysis using fruits, the results obtained in the condition of LS1 were all better than that of LS2, and the best results were correlation coefficient of calibration (r_c) = 0.948, root mean square error of calibration (RMSEC)= 0.299°Brix, correlation coefficient of cross-validation (r_(cv))-0.924, and root mean square error of cross-validation (RMSECV) = 0.359°Brix. This was well matched to the results of SNR and ACR analysis. This study demonstrates that SNR and ACR of spectra can be used to evaluate the reasonable of the Vis/NIR spectral measuring system.
机译:光谱测量系统的稳定性在工厂级可见光和近红外(Vis / NIR)光谱仪对农产品的无损内部质量测量中非常重要。但是,关于如何评估光谱测量系统是否合理的著作很少。在本文中,参考标准光谱的信噪比(SNR)和面积变化率(ACR)用于评估Vis / NIR光谱系统。考虑了具有不同光源的两个不同系统(LSI和LS2)。结果表明,在LSI条件下在每个选定波长处记录的SNR均高于LS2条件下记录的SNR,在LS1条件下550 nm至920 nm之间的ACR小于LS2。同时,在通过水果的校正和交叉验证分析进行的验证实验中,在LS1条件下获得的结果均优于LS2,并且最佳结果是校正的相关系数(r_c)= 0.948,均方根校准误差(RMSEC)= 0.299°Brix,交叉验证的相关系数(r_(cv))-0.924,交叉验证的均方根误差(RMSECV)= 0.359°Brix。这与SNR和ACR分析的结果非常匹配。这项研究表明,光谱的SNR和ACR可用于评估Vis / NIR光谱测量系统的合理性。

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