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Tracing the Geographical Origin of Durum Wheat by FT-NIR Spectroscopy

机译:FT-NIR光谱法追踪硬粒小麦的地理起源

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Fourier transform near infrared (FT-NIR) spectroscopy, in combination with principal component-linear discriminant analysis (PC-LDA), was used for tracing the geographical origin of durum wheat samples. The classification model PC-LDA was applied to discriminate durum wheat samples originating from Northern, Central, and Southern Italy ( n = 181), and to differentiate Italian durum wheat samples from those cultivated in other countries across the world ( n = 134). Developed models were validated on a separated set of wheat samples. Different pre-treatments of spectral data and different spectral regions were selected and compared in terms of overall discrimination (OD) rates obtained in validation. The LDA models were able to correctly discriminate durum Italian wheat samples according to their geographical origin (i.e., North, Central, and South) with OD rates of up of 96.7%. Better results were obtained when LDA models were applied to the discrimination of Italian durum wheat samples from those originating from other countries across the world, having OD rates of up to 100%. The excellent results obtained herein clearly indicate the potential of FT-NIR spectroscopy to be used for the discrimination of durum wheat samples according to their geographical origin.
机译:傅里叶变换近红外光谱(FT-NIR)与主成分线性判别分析(PC-LDA)结合用于追踪硬粒小麦样品的地理起源。分类模型PC-LDA用于区分源自意大利北部,中部和南部的硬粒小麦样品(n = 181),并将意大利硬粒小麦样品与世界其他国家/地区种植的硬粒小麦样品(n = 134)区分开来。在一组单独的小麦样品上验证了开发的模型。选择不同的光谱数据预处理和不同的光谱区域,并根据验证中获得的总分辨率(OD)进行比较。 LDA模型能够根据其原产地(即北部,中部和南部)正确区分硬粒意大利小麦样品,OD率高达96.7%。当将LDA模型应用于意大利硬质小麦样品与来自世界其他国家的样品的OD率高达100%的鉴别时,可获得更好的结果。本文获得的出色结果清楚地表明了FT-NIR光谱技术可根据其地理来源用于鉴别硬质小麦样品的潜力。

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