基于可见/近红外光谱无损检测苹果可溶性固形物的光照优化

Optimization of light distribution in non-destructive analysis of soluble solids content of apple base on visual/near-infrared spectroscopy

为优化光照在提高可见/近红外光谱无损检测苹果可溶性固形物含量(SSC)精度中的应用,实验比较了四种光照方式对USB2000+微型光谱仪采集苹果随机摆放位置时的透射光谱信号。在剔除光谱异常样本并经光谱预处理后,与常规方法检测的SSC建立偏最小二乘(PLS)回归模型。通过比较模型的预测均方根误差(RMSEP)与相关系数(rp),结果发现低角度、多光源组合的光照方式最好,模型预测结果为rp=0.804、RMSEP=0.635。该光照方式可为今后便携装置、在线检测的光源设计提供参考。

To optimize the distribution of light source in the aspect of non-invasive analysis of soluble solids content （SSC） by visual/near-infrared （Vis/NIR） transmittance, four arrangements of light source distribution were designed to diminish the influence of the random acquisition-spot on ＇Red Fuji＇ apple by USB2000＋ portable fiber spectroscopy. After getting rid of the outliers and several pre-treatments on the transmitted spectra,partial least square（PLS） models were built between the spectra and the SSC,which was determined by regular method. Comparison of models＇ root meant standard error prediction （RMSEP） and correlation coefficient （rp）,it was found that the type of that low angle of light illumination combined with multi-light sources was the best one to show the internal qualities of the fruit,with the corresponding prediction model for SSC as r0=0.804,as well as RMSEP=0.635. This might be a good reference to light-source distribution for online or portable device non-destructive determination used for industrial applications.