Determining the geographic origin of wheat using multielement analysis and multivariate statistics

Area of Science:

• Agricultural Chemistry
• Analytical Chemistry
• Food Science

Background:

• Wheat origin traceability is crucial for food safety and quality control.
• Geographical origin can influence wheat's elemental composition.
• Understanding elemental profiles aids in authenticating wheat sources.

Purpose of the Study:

• To classify wheat based on geographical origin using elemental analysis.
• To investigate the influence of region, variety, and harvest year on wheat's element content.
• To assess the efficacy of multielement analysis for wheat origin determination.

Main Methods:

• Inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the concentrations of 15 elements in 240 wheat samples.
• Multivariate statistical analyses, including analysis of variance (ANOVA) and linear discriminant analysis (LDA), were applied.
• Wheat samples were collected from four major Chinese wheat-producing regions over two harvest years (2007/2008 and 2008/2009).

Main Results:

• Significant differences in element content were observed across different wheat-producing regions.
• Elemental profiles varied significantly based on wheat variety and harvest year.
• A discriminant model was developed to classify wheat origin with a certain degree of accuracy.

Conclusions:

• Multielement analysis is a viable and promising method for providing reliable geographical origin information for wheat.
• Wheat variety, harvest year, and agricultural practices can affect elemental profiles and the accuracy of origin classification.
• Further refinement of models considering these factors is necessary for enhanced accuracy.