利用近红外光谱技术检测掺假豆浆

为了对豆乳内在营养指标及掺假豆乳进行快速检测，试验运用近红外光谱技术，利用偏最小二乘法进行回归分析，分别建立83个真伪豆浆样品的蛋白质和总固形物含量定标模型，并对模型的预测性能进行分析。结果表明：选取主成分数为12和14，蛋白质和总固形物含量的近红外光谱预测值与化学实测值之间的相关系数R分别为0．9756和0．9489，校正均方根误差分别为0．186和0．175，预测集样品的预测值和实测值之间的残差值均较小、接近零，残差之和分别为-0．074和-1．191，说明建立的定标模型可以准确预测豆浆中蛋白质和总固形物含量，且预测性能较好；通过对预测集样品的预测值与豆浆行业标准规定值相比较，确定预测集样...

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Bibliographic Details
Published in农业工程学报 Vol. 30; no. 3; pp. 238 - 242
Main Author 李东华 潘园园 张卉
Format Journal Article
LanguageChinese
Published 沈阳化工大学制药与生物工程学院,沈阳,110142 2014
Subjects
总固形物
掺假检测
无损检测
蛋白质
豆浆
近红外光谱
豆浆
nondestructive examination
total solids content
近红外光谱
总固形物
proteins
掺假检测
near infrared spectroscopy
soymilk
adulteration detection
无损检测
蛋白质
Online AccessGet full text
ISSN1002-6819
DOI10.3969/j.issn.1002-6819.2014.03.031

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Summary:为了对豆乳内在营养指标及掺假豆乳进行快速检测，试验运用近红外光谱技术，利用偏最小二乘法进行回归分析，分别建立83个真伪豆浆样品的蛋白质和总固形物含量定标模型，并对模型的预测性能进行分析。结果表明：选取主成分数为12和14，蛋白质和总固形物含量的近红外光谱预测值与化学实测值之间的相关系数R分别为0．9756和0．9489，校正均方根误差分别为0．186和0．175，预测集样品的预测值和实测值之间的残差值均较小、接近零，残差之和分别为-0．074和-1．191，说明建立的定标模型可以准确预测豆浆中蛋白质和总固形物含量，且预测性能较好；通过对预测集样品的预测值与豆浆行业标准规定值相比较，确定预测集样品中掺假豆浆的正确判别率为100％，说明建立的蛋白质和总固形物含量定标模型可以应用于掺假豆浆的判别检测，且判别结果准确率高。本试验表明利用近红外光谱技术可实现对豆浆主要品质指标的快速无损检测，也可准确进行真伪豆浆的快速判别，本检测方法可为豆乳行业健康持续发展提供一定的技术支撑。
Bibliography:11-2047/S
In order to rapidly detect the internal nutritive index and discriminate adulteration soymilk, the near infrared transmission spectrometer such as Purespect was used to obtain spectrums for 83 unadulterated and adulterated soymilk samples. The spectral scanning procedure was conducted in dark room, 643.26-954.15 nm wavelength range was chosen, scanning wavelength interval was 1.29 nm. Each soymilk sample was scanned three times. Pure soymilks were made according to the regulations in soymilk products industry standard SB/T 10633-2011. A lot of water, essence, thickening agent, food sunset yellow pigment were added to unadulterated soymilk samples in order to obtain adulterated soymilk samples. In this study, 31 adulteration samples and 62 unadulterated samples were prepared in the processing laboratories. 14 soymilk samples were gathered from the market. All samples were used to scan the spectrum and determining chemical composition. The experimental results indicated that smooth lines and clear spec
ISSN:1002-6819
DOI:10.3969/j.issn.1002-6819.2014.03.031