Department of Industrial Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia.
Davutpaşa Campus, Chemical and Metallurgical Engineering Faculty, Food Engineering Department, Yıldız Technical University, Istanbul, Turkey.
J Sci Food Agric. 2021 Mar 15;101(4):1699-1708. doi: 10.1002/jsfa.10845. Epub 2020 Oct 21.
Ground pistachio nut is prone to adulteration because of its high economic value and wide usage. Green pea is known as the main adulterant in frauds involving pistachio nuts. The present study developed a new, rapid, reliable and low-cost methodology by using a portable Raman spectrometer in combination with chemometrics for the detection of green pea in pistachio nuts.
Three different methods of Raman spectroscopy-based chemometrics analysis were developed for the determination of green-pea adulteration in pistachio nuts. The first method involved the development of hierarchical cluster analysis (HCA) and principal component analysis (PCA), which differentiated authentic pistachio nuts from green pea and green pea-adulterated samples. The best classification pattern was observed in the adulteration range of 20-80% (w/w). In addition to classification methods, partial least squares regression (PLSR) and genetic algorithm-based inverse least squares (GILS) were also used to develop multivariate calibration models to determine quantitatively the degree of green-pea adulteration in grounded pistachio nuts. The spectral range of 1790-283 cm was used in the case of multivariate data analysis. A green-pea adulteration level of 5-80% (w/w) was successfully identified by PLSR and GILS. The correlation coefficient of determination (R ) was determined as 0.91 and 0.94 for the PLSR and GILS analyses, respectively.
A Raman spectrometer combined with chemometrics has a high capability with regard to the detection of adulteration in pistachio nuts, combined with low cost, strong reliability, a high level of accuracy, rapidity of analysis, and minimum sample preparation. © 2020 Society of Chemical Industry.
由于具有较高的经济价值和广泛的用途，开心果很容易被掺假。青豆是开心果掺假中常见的掺杂物。本研究采用便携式拉曼光谱仪结合化学计量学，建立了一种新的、快速、可靠且低成本的方法，用于检测开心果中的青豆。
开发了三种基于拉曼光谱化学计量学分析的不同方法，用于确定开心果中绿豌豆的掺假情况。第一种方法涉及层次聚类分析（HCA）和主成分分析（PCA）的开发，可区分纯开心果和青豆及青豆掺假样品。在 20-80%（w/w）的掺假范围内观察到最佳分类模式。除分类方法外，还使用偏最小二乘回归（PLSR）和基于遗传算法的逆最小二乘（GILS）建立多元校准模型，以定量确定磨碎开心果中绿豌豆的掺假程度。多元数据分析中使用了 1790-283 cm 的光谱范围。PLSR 和 GILS 成功识别了 5-80%（w/w）的绿豌豆掺假水平。PLSR 和 GILS 分析的决定系数（R ）分别为 0.91 和 0.94。
拉曼光谱仪结合化学计量学在检测开心果掺假方面具有很高的能力，具有成本低、可靠性强、准确度高、分析速度快、样品制备量少等优点。 © 2020 化学工业协会。
