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首页> 外文期刊>Food and Chemical Toxicology: An International Journal Published for the British Industrial Biological Research >Geographical discrimination of garlic (Allium Sativum L.) based on Stable isotope ratio analysis coupled with statistical methods: The Italian case study
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Geographical discrimination of garlic (Allium Sativum L.) based on Stable isotope ratio analysis coupled with statistical methods: The Italian case study

机译:基于稳定同位素比率分析的大蒜(Allium Sativum L.)与统计方法的地理辨别:意大利案例研究

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摘要

Stable isotope ratio analysis of the major bioelements (delta H-2, delta C-13, delta N-15, delta O-18, delta S-34), considered for the first time as a whole, was used to attempt a geographical characterization of red garlic (Allium sativum L.) cultivated throughout different Italian territories (Abruzzo, Lazio and Sicily). Up to now, no official methods are available to determine the geographical origin of this type of product. In this context, the Isotope Ratio Mass Spectrometry method (IRMS) represents a powerful analytical technique. The characteristic ranges of variability of the five isotope ratios in 56 red Italian garlic samples are here presented as well as their relationships. The geographical origin has some influence over the different ratios, although their data distribution shows some overlap when Principal Component Analysis (PCA) is applied. In spite of the relative closeness of the sampling sites, a model with very good predictive performance of the geographical classification was achieved byLinear Discriminant Analysis (LDA) and k-nearest neighbours (k-NN) method. Moreover, preliminary class modelling based on Soft Independent Modelling of Class Analogy (SIMCA) supports the ability of stable isotope ratios analysis for the geographical traceability of garlic.
机译:稳定的同位素比例分析主要生物元素(Delta H-2,Delta C-13,Delta N-15,Delta O-18,Delta S-34),作为一个整体认为是尝试地理位置在整个意大利地区(Abruzzo,Lazio和Sicily)栽培的红色大蒜(Allium Sativum L.)的特征。到目前为止,没有官方方法可用于确定此类产品的地理来源。在这种情况下,同位素比质谱法(IRMS)表示强大的分析技术。此处呈现了56个红色意大利大蒜样品中的五个同位素比的变异性的特征范围以及它们的关系。地理原点对不同比率产生了一些影响,尽管当应用主成分分析(PCA)时,它们的数据分布显示了一些重叠。尽管采样位点的相对近闭合,但通过线性判别分析(LDA)和K-Nember邻居(K-NN)方法,实现了具有非常好的预测性能的模型。此外,基于类比(SIMCA)软独立建模的初步类建模支持稳定同位素比率分析大蒜的地理可追溯性。

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