首页> 外文期刊>Journal of near infrared spectroscopy >Potential of near infrared transflectance spectroscopy to detect adulteration of Irish honey by beet invert syrup and high fructose corn syrup
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Potential of near infrared transflectance spectroscopy to detect adulteration of Irish honey by beet invert syrup and high fructose corn syrup

机译:近红外半透射光谱法可检测甜菜倒糖浆和高果糖玉米糖浆对爱尔兰蜂蜜的掺假

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Near infrared (1100-2498 nm) transflectance spectroscopy was used to detect beet invert syrup (BI) and high fructose corn syrup (HFCS) adulterants in artisanal Irish honey. The sample set investigated comprised authentic (n=83), Bl-adulterated (n=56) and HFCS-adulterated (n=40) honeys. Soft independent modelling of class analogy was used to classify honeys as authentic or adulterated while partial least squares regression (PLS1) was used to predict the adulteration level. Spectral data were investigated in three forms: raw, after multiplicative scatter correction and after second derivative transformation. The best classification model was obtained using raw spectral data. The preferred models for prediction of percentage adulteration involved PLS1 of multiplicative scatter corrected spectra (adulteration with BI) and second derivative transformation (adulteration with HFCS). The present study has demonstrated that near infrared spectroscopy could be used as a rapid screening tool for detection of BI and HFCS adulteration in Irish honey.
机译:使用近红外(1100-2498 nm)透射光谱法检测爱尔兰手工蜂蜜中的甜菜反相糖浆(BI)和高果糖玉米糖浆(HFCS)掺杂物。所研究的样品集包括纯正蜂蜜(n = 83),B1掺杂的(n = 56)和HFCS掺杂的(n = 40)蜂蜜。使用类比的软独立模型将蜂蜜分类为真实蜂蜜或掺假蜂蜜,同时使用偏最小二乘回归(PLS1)预测掺假水平。光谱数据以三种形式进行研究:原始,乘法散射校正后和二阶导数变换后。最佳分类模型是使用原始光谱数据获得的。预测掺假百分比的首选模型涉及乘法散射校正光谱的PLS1(使用BI进行掺入)和二阶导数变换(使用HFCS进行掺入)。本研究表明,近红外光谱法可用作检测爱尔兰蜂蜜中BI和HFCS掺假的快速筛选工具。

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