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首页> 外文期刊>Journal of Food Measurement and Characterization >Non-targeted approach to detect green pea and peanut adulteration in pistachio by using portable FT-IR, and UV-Vis spectroscopy
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Non-targeted approach to detect green pea and peanut adulteration in pistachio by using portable FT-IR, and UV-Vis spectroscopy

机译:通过使用便携式FT-IR和UV-Vis光谱法检测青叶和花生掺杂的非靶向方法

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Pistachio is one of the most expensive nuts with having high economic importance in Turkey. It has become more prone to adulteration because of its high commodity value. Peanut with color additives and green pea are generally used to adulterate ground pistachio. Vibrational spectroscopy is a potential technique to detect adulterations in pistachio. The objective of this study was to generate a non-targeted method for portable FT-IR and UV-Vis spectrometers to authenticate pistachio and detect green pea and peanut adulterations. Pistachio granules were adulterated with green pea and peanut at different concentrations (5 to 40% w/w). Spectra were collected by a portable FT-IR spectrometer and by a conventional UV-Vis spectrometer and analyzed by Soft Independent Modeling of Class Analogy (SIMCA) to generate classification algorithms to authenticate pistachio, and Partial Least Square Regression (PLSR) to predict the concentrations of adulterants. SIMCA showed very distinct clusters for pure samples. Moreover, adulterated pistachio samples were discriminated by SIMCA even in low levels of adulteration (5%). Portable FTIR showed excellent performance (r(val) > 0.93) of predicting the adulterant levels with a standard error of prediction (SEP) 0.66% and 0.80% for green pea and peanut, respectively. Similarly, UV-VIS predicted (r(val) > 0.93) the adulterant levels with SEP 0.58% and 0.14% for green pea and peanut, respectively. The results supported that portable FT-IR, and UV-Vis units present great potential for real-time surveillance of green pea and peanut adulteration in pistachio.
机译:开心果是土耳其最昂贵的坚果之一,具有很高的经济价值。由于其商品价值高,它更容易被掺假。添加着色剂的花生和青豆通常被用于掺杂磨碎的开心果。振动光谱法是检测开心果掺假的一种潜在技术。本研究的目的是为便携式FT-IR和UV-Vis光谱仪建立一种非靶向方法,以鉴定阿月浑子并检测绿豌豆和花生掺假。在开心果颗粒中掺入不同浓度(5-40%w/w)的青豆和花生。通过便携式FT-IR光谱仪和常规紫外-可见光谱仪收集光谱,并通过类类比软独立建模(SIMCA)进行分析,以生成分类算法来验证阿月浑子,并通过偏最小二乘回归(PLSR)预测掺假物的浓度。SIMCA对纯样品显示出非常明显的聚类。此外,即使在较低的掺假水平(5%)下,SIMCA也能鉴别出掺假的阿月浑子样品。便携式FTIR显示出良好的性能(r(val)>0.93),对青豆和花生的预测标准误差(SEP)分别为0.66%和0.80%。同样,UV-VIS预测(r(val)>0.93)绿豆和花生的掺杂水平分别为0.58%和0.14%。结果支持便携式FT-IR和UV-Vis装置在实时监测开心果中的绿豌豆和花生掺假方面具有巨大潜力。

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