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中国精品科技期刊2020
冯尚坤, 徐海菊. 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[J]. 食品工业科技, 2014, (16): 64-66. DOI: 10.13386/j.issn1002-0306.2014.16.005
引用本文: 冯尚坤, 徐海菊. 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[J]. 食品工业科技, 2014, (16): 64-66. DOI: 10.13386/j.issn1002-0306.2014.16.005
FENG Shang-kun, XU Hai-ju. Optimization of light distribution in non-destructive analysis of soluble solids content of apple base on visual/near-infrared spectroscopy[J]. Science and Technology of Food Industry, 2014, (16): 64-66. DOI: 10.13386/j.issn1002-0306.2014.16.005
Citation: FENG Shang-kun, XU Hai-ju. Optimization of light distribution in non-destructive analysis of soluble solids content of apple base on visual/near-infrared spectroscopy[J]. Science and Technology of Food Industry, 2014, (16): 64-66. DOI: 10.13386/j.issn1002-0306.2014.16.005

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

  • 摘要: 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。 

     

    Abstract: 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 rp=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.

     

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