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The stable isotope and multi-element are effective fingerprints for identifying geographic origin of foodstuff, but it is unclear that how the fingerprints information is affected by factors such as region, genotype, harvest year and so on. Wheat was selected as model plant in this study based on its wide distribution, diverse varieties and genetic uniformity. Experiments with ten genotypes of wheat were carried out in three different regions (Zhaoxian, Huixian, and Yangling) of China in three consecutive growing seasons (2010-2012), with totally 270 wheat kernel samples collected. The stable isotopes (d13C, d15N and dD) and multi-elemental compositions (Mg, Al, Ca, Mn, Fe, Cu, Zn, As, Sr, Mo, Cd, Ba, Pb) were analyzed to investigate the effects and contributions of wheat origin, genotype, harvest year and their interactions on fingerprints for wheat kernels. All the fingerprints were found to be significantly influenced by wheat origin, genotype, harvest year and their interactions using analysis of variances. Region accounted for the largest proportion of the total variation for d13C, d15N, dD, Mn, Sr, Mo, Cd in wheat, and genotypes showed the largest variation contribution for Ba, accounting for 27.34%. Error provided the most variation for Pb, representing 43.13%. Notably, the harvest year provided the most variation for other elements (Mg, Al, Ca, Fe, Cu, Zn and As), explaining 33.65, 29.70, 66.30, 56.88, 56.82, 36.55 and 51.51%, respectively. Geographical traceability of wheat can be successfully realized (100%) using a robust discrimination model with seven indicators (d13C, d15N, dD, Mn, Sr, Mo, Cd) even for wheat from different genotypes and harvest years. This research confirms the validity of geographical traceability using fingerprints and provides powerful theoretical proof for understanding the role of genotype, harvest year on geographical traceability.