蓝莓可溶性固形物、总酚和花青素近红外光谱检测技术研究
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摘要
蓝莓属杜鹃花科(Ericaceae)越橘属(Vaccinium Linn.),是深受人们喜爱的水果之一。对其品质的研究多采用有损伤的化学方法测定,存在制样繁琐、分析时间长及检测成本高等缺点。近红外光谱技术具有方便、快速、无损伤、信息量大等特点,近年来在果蔬内部品质检测中得到了广泛的研究和应用。本论文应用傅里叶变换近红外漫反射光谱技术,建立了蓝莓可溶性固形物含量、总酚含量和花青素含量的定量分析模型,确定了最佳建模参数。主要研究结果如下：
(1)利用近红外漫反射光谱技术检测蓝莓可溶性固形物含量。有效信息波谱范围为4000cm-～10000cm-1,对原始光谱采用一阶导数处理,主成分分析得到主成分数为3,由偏最小二乘法所建校正模型的预测效果好,模型的相关系数为0.91518,校正集标准偏差RMSEP为0.801。应用此模型对验证集27个样本进行预测,预测标准偏差RMSEP为1.06。结果表明校正模型的预测效能满足蓝莓可溶性固形物含量快速检测的要求。
(2)利用近红外漫反射光谱技术检测蓝莓总酚含量。有效信息波谱范围为4000cm-1～10000cm-1,主成分数为3,对整体平均光谱应用一阶导数结合偏最小二乘法所建校正模型的预测效果好,模型的相关系数为0.95118,RMSEC为0.72。应用此模型对验证集27个样本进行预测,RMSEP为0.93。结果表明模型预测效果能满足蓝莓总酚含量快速检测的要求。
(3)利用近红外漫反射光谱技术检测蓝莓花青素含量。在有效信息波谱范围为4000cm-1～10000cm-1,及主成分数选择5时对整体平均光谱应用一阶导数结合偏最小二乘法所建校正模型的预测效果好,模型的相关系数为0.927,RMSEC为0.54。应用此模型对验证集12个样本进行预测,RMSEP为0.55。结果表明模型预测效果能满足蓝莓花青素含量快速检测的要求。
Blueberry (family Ericaceae; genus Vaccinium Linn.) is one of the favorite fruits for consumers. Chemical methods are the common ways for the detection of its quality, but there are a lot of shortcomings such as complicated ways of sample preparation, time-consuming analysis and high cost. During these years Near Infrared spectroscopy has been widely used for quality determination of fruits and vegetables owing to its advantages such as convenience, rapidness, non-destruction and full of abundant information. The objective of this research was to establish quantitative models for rapid measurements of soluble solids content, total phenol and anthocyanins in blueberry using Fourier Transform NIR diffuse reflectance spectroscopy. The main results are as follows:
(1)Using NIR diffuse reflectance spectroscopy as a rapid and non-destructive method for the determination of soluble solids content of blueberry, the results showed that the best statistical model was developed using partial least square method with1st derivative and3as the No. of factors in the wave number range of4000cm-1-10000cm-1.The correlation coefficient(R) of themodel was0.91518and the root mean square error of calibration (RMSEC) was0.801.Using the model to validate27samples, the results showed that the root mean square error of prediction (RMSEP) was1.06. It was concluded that the prediction of the model can meet the requirement of rapid measuring of blueberry's soluble solids content.
(2)Using NIR diffuse reflectance spectroscopy as a rapid and non-destructive method for the determination of total phenol contents of blueberry, the results showed that the best statistical model was developed using PLS with respect to first derivative and3as the No. of factors in the wave number range of4000cm-1-10000cm-1. R of the model was0.95118and RMSEC was0.72. Using the model to validate27samples, the results showed that RMSEP was0.93. It was concluded that the prediction of the model can meet the requirement of rapid measuring of blueberry's the total phenol contents.
(3)Using NIR diffuse reflectance spectroscopy as a rapid and non-destructive method for the determination of anthocyanins of blueberry, the results showed that the best statistical model was developed using PLS with respect to first derivative and5as No. of factors in the wave number range of4000c4000cm-1～100000cm-1. R of the model was0.927and RMSEC was0.54. Using the model to validate12samples, the results showed that RMSEP was0.55. It was concluded that the prediction of the modelcan meet the requirement of rapid measuring of blueberry's anthocyanins.
(1)利用近红外漫反射光谱技术检测蓝莓可溶性固形物含量。有效信息波谱范围为4000cm-～10000cm-1,对原始光谱采用一阶导数处理,主成分分析得到主成分数为3,由偏最小二乘法所建校正模型的预测效果好,模型的相关系数为0.91518,校正集标准偏差RMSEP为0.801。应用此模型对验证集27个样本进行预测,预测标准偏差RMSEP为1.06。结果表明校正模型的预测效能满足蓝莓可溶性固形物含量快速检测的要求。
(2)利用近红外漫反射光谱技术检测蓝莓总酚含量。有效信息波谱范围为4000cm-1～10000cm-1,主成分数为3,对整体平均光谱应用一阶导数结合偏最小二乘法所建校正模型的预测效果好,模型的相关系数为0.95118,RMSEC为0.72。应用此模型对验证集27个样本进行预测,RMSEP为0.93。结果表明模型预测效果能满足蓝莓总酚含量快速检测的要求。
(3)利用近红外漫反射光谱技术检测蓝莓花青素含量。在有效信息波谱范围为4000cm-1～10000cm-1,及主成分数选择5时对整体平均光谱应用一阶导数结合偏最小二乘法所建校正模型的预测效果好,模型的相关系数为0.927,RMSEC为0.54。应用此模型对验证集12个样本进行预测,RMSEP为0.55。结果表明模型预测效果能满足蓝莓花青素含量快速检测的要求。
Blueberry (family Ericaceae; genus Vaccinium Linn.) is one of the favorite fruits for consumers. Chemical methods are the common ways for the detection of its quality, but there are a lot of shortcomings such as complicated ways of sample preparation, time-consuming analysis and high cost. During these years Near Infrared spectroscopy has been widely used for quality determination of fruits and vegetables owing to its advantages such as convenience, rapidness, non-destruction and full of abundant information. The objective of this research was to establish quantitative models for rapid measurements of soluble solids content, total phenol and anthocyanins in blueberry using Fourier Transform NIR diffuse reflectance spectroscopy. The main results are as follows:
(1)Using NIR diffuse reflectance spectroscopy as a rapid and non-destructive method for the determination of soluble solids content of blueberry, the results showed that the best statistical model was developed using partial least square method with1st derivative and3as the No. of factors in the wave number range of4000cm-1-10000cm-1.The correlation coefficient(R) of themodel was0.91518and the root mean square error of calibration (RMSEC) was0.801.Using the model to validate27samples, the results showed that the root mean square error of prediction (RMSEP) was1.06. It was concluded that the prediction of the model can meet the requirement of rapid measuring of blueberry's soluble solids content.
(2)Using NIR diffuse reflectance spectroscopy as a rapid and non-destructive method for the determination of total phenol contents of blueberry, the results showed that the best statistical model was developed using PLS with respect to first derivative and3as the No. of factors in the wave number range of4000cm-1-10000cm-1. R of the model was0.95118and RMSEC was0.72. Using the model to validate27samples, the results showed that RMSEP was0.93. It was concluded that the prediction of the model can meet the requirement of rapid measuring of blueberry's the total phenol contents.
(3)Using NIR diffuse reflectance spectroscopy as a rapid and non-destructive method for the determination of anthocyanins of blueberry, the results showed that the best statistical model was developed using PLS with respect to first derivative and5as No. of factors in the wave number range of4000c4000cm-1～100000cm-1. R of the model was0.927and RMSEC was0.54. Using the model to validate12samples, the results showed that RMSEP was0.55. It was concluded that the prediction of the modelcan meet the requirement of rapid measuring of blueberry's anthocyanins.
引文
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