The effectiveness of multi‐element fingerprints for identifying the geographical origin of wheat

Liu, Hongyan; Wei, Yimin; Zhang, Yingquan; Wei, Stephen H.Y.; Zhang, Senshen; Guo, Bin

doi:10.1111/ijfs.13366

Cited by 22 publications

(10 citation statements)

References 30 publications

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“…Apart from the factor of the genotype, the concentrations of most elements (Na, Mg, Al, K, Ca, Mn, Fe, Co, Zn, As, Rb, and Sr) were found to be significantly different among two years. In previous reports, the contents of Mg, Al, Ca, Fe, Zn, and As in wheat were most affected by the harvest year comparing with the region or genotype according to the result of multiway variance analysis [19], and the harvest year was the main source of the variations of the concentrations of Fe and Zn in maize [28]; these results are consistent with ours. e significant differences for some element contents could be explained by the changing weather conditions such as the annual temperature, precipitation, and sunshine.…”

Section: Discussionsupporting

confidence: 91%

“…e elements in plants are mainly from the surroundings (water and soil). Due to the di erences in hydrological characteristics and geological background, di erent plants have di erent element pro les, which provide the possibility of the geographical traceability for foodstu including both plants and animals [19]. is technique had been applied to identify the geographical origins of cereals including wheat [16] and rice [1,15,20,21].…”

Section: Introductionmentioning

confidence: 99%

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Determination of Geographical Origin of Wuchang Rice with the Geographical Indicator by Multielement Analysis

Qian

Zuo

Liu

et al. 2019

Journal of Food Quality

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The study aims to investigate whether the multielement analysis result can be used as a fingerprint to identify the geographical origin of Wuchang rice. The element contents of rice and soil samples from three regions in China (Wuchang, Qiqihar, and Jiamusi) were analyzed. The concentrations of 16 elements (Na, Mg, Al, K, Ca, V, Mn, Fe, Co, Cu, Zn, As, Rb, Sr, Cd, and Pb) in 194 rice samples and 112 soil samples from the harvest season in 2013 and 2014 were determined. The analysis of variance and linear discriminant analysis were performed to analyze the variation among regions and rice genotypes and classify the geographical origins of rice. Only the element of Cu showed significant differences among different genotypes. In the discriminant analysis, the overall correct identification rates of the rice samples obtained in 2013 and 2014 were, respectively, 96.6% and 89.6% and the overall correct identification rate for Wuchang rice reached 100%.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Determination of Geographical Origin of Wuchang Rice with the Geographical Indicator by Multielement Analysis

Qian

Zuo

Liu

et al. 2019

Journal of Food Quality

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“…In the past few years, analytical techniques for geographical traceability have made a significant progress. A wide range of agro-products have been discriminated successfully using a combination of chemometrics and several analytical techniques such as spectrometry techniques (GC-MS, IRMS, ICP-MS), separation technique (HPLC; Scampicchio et al, 2012;Liu et al, 2017b;Sabir et al, 2017;Lim et al, 2018). In addition, spectroscopic techniques (NIR, FTIR, NMR) have been applied to various food products to investigate the authenticity and geographical origin (Tapp et al, 2003;Sun et al, 2012;Longobardi et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Geographical origin discrimination of wheat kernel and white flour using near‐infrared reflectance spectroscopy fingerprinting coupled with chemometrics

Wadood

Guo

Zhang

et al. 2019

Int J of Food Sci Tech

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Summary Wheat kernel and flour with three genotypes across 4 years procured from three different geographical areas of China were analysed using near‐infrared reflectance (NIR) spectroscopy coupled with chemometrics to better classify wheat according to the origin, production year and genotypes, respectively. For this purpose, principle component analysis‐linear discriminant analysis and multi‐way anova were applied to the NIR data. The best classification percentages were obtained for flour matrix both for geographical origin and production years with the correct percentages of 100% and 73%, respectively. For genotypes, wheat whole kernel showed better classification percentage (98.2%). All the samples were validated using external validation procedure and the obtained percentages were found satisfactory with the average prediction abilities of >85% in all regions indicating the suitability of the developed model. Multivariate anova showed that NIR fingerprints of wheat kernels and flours were significantly influenced by regions, years, genotypes and their interactions. In conclusion, white flour showed better performance in discriminating the geographical origin as compared to wheat whole kernel.

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“…Both reported values were below the WHO standard [44, 48]. Moreover, geographic differences between samples and nature of soil and water can cause variation among results of different studies [49]. Also, the concentrations of elements detected do not exceed the recommended values of the WHO [44].…”

Section: Discussionmentioning

confidence: 99%

Estimated dietary intake of essential elements from four selected staple foods in Najran City, Saudi Arabia

2019

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The estimated dietary intake ( EDI) of essential elements selenium (Se), zinc (Zn), manganese (Mn) and copper (Cu) has not been previously investigated for Najran city, Saudi Arabia. This type of information can be valuable for protecting public health. The aim of this study was to estimate the EDI of these elements. A food frequency questionnaire (FFQ) was completed by the study participants (n = 80) to obtain dietary intake of selected staple foods (rice, wheat, meat and chicken). The concentrations of Se, Zn, Mn and Cu in these staple foods were determined using inductively coupled plasma-mass spectrometry (ICP-MS). The ranges of concentrations (mg/kg, wet weight) were as follows: Se (0.07–0.24), Zn (3.91–20.89), Mn (0.63–14.69) and Cu (0.69–2.41). The calculated ranges of EDIs (mg/kg bw/day) for the essential elements were as follows: Se 9.55 × 10 −5 –5.75 × 10 −4 , Zn 1.33 × 10 −2 –5.83 × 10 −2 , Mn 1.49 × 10 −3 –3.31 × 10 −2 , Cu 1.65 × 10 −3 –5.42 × 10 −3 . The highest EDI for Cu and Mn came from wheat. In the case of Se and Zn, the foods that contributed the highest EDI were chicken and meat, respectively. The lowest EDIs were found for Se in wheat, Zn in rice and both Mn and Cu in chicken. The percentages (%) of provisional maximum tolerable daily intake (PMTDI) for Se, Zn, Mn and Cu were 13%, 11%, 14% and 3.4%, respectively when contributions from all the four classes of foods were combined. The percentage of the recommended daily allowance (RDA) derived from these foods were 80%, 20%, 17% and 5.6% for Se, Zn, Mn and Cu were, respectively. This raises the possibility of Cu deficiency in the Najran population. However, a total diet study and human biomonitoring study is needed in the future to fully assess if people in Najran city are at risk of deficiency or excessive exposure to trace elements.

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The effectiveness of multi‐element fingerprints for identifying the geographical origin of wheat

Cited by 22 publications

References 30 publications

Determination of Geographical Origin of Wuchang Rice with the Geographical Indicator by Multielement Analysis

Determination of Geographical Origin of Wuchang Rice with the Geographical Indicator by Multielement Analysis

Geographical origin discrimination of wheat kernel and white flour using near‐infrared reflectance spectroscopy fingerprinting coupled with chemometrics

Estimated dietary intake of essential elements from four selected staple foods in Najran City, Saudi Arabia

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