Determining the geographical origin of Chinese cabbages using multielement composition and strontium isotope ratio analyses

Bong, Yeon-Sik; Shin, Woojin; Gautam, Mukesh Kumar; Jeong, Youn-Joong; Lee, Areum; Jang, Chang-Hwan; Lim, Yong-Pyo; Chung, Gong Soo; Lee, Kwang-Sik

doi:10.1016/j.foodchem.2012.07.045

Cited by 62 publications

(32 citation statements)

References 27 publications

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“…The elements in the soil samples in order of descending content are as follows: K, Na, Ca, Fe, Mg, Mn, Zn, and Cu. This result is consistent with prior findings (Bong and others ). A significant connection between plant and soil elemental composition has been reported in literature (Furia and others ).…”

Section: Resultssupporting

confidence: 94%

“…Multielement testing is one of the most common techniques because of its high reproducibility. This technique, followed by multivariate data analysis, has been employed to characterize the elemental profiles of beef (Franke and others ), mutton (Sun and others ), olive oil (Camin and others ), wheat (Khoshgoftarmanesh and others ), cabbage (Bong and others ), rice (Li and others ), honey (Tuzen and others ), coffee (Muñiz‐Valencia and others ), and wine (Rodrigues and others ; Geana and others ). In addition, multielement testing is particularly sensitive to the soil and climate conditions under which agricultural crops are grown.…”

Section: Introductionmentioning

confidence: 99%

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Identification of the Geographical Origins of Pomelos Using Multielement Fingerprinting

Yan

Liu

Xiong

et al. 2015

Journal of Food Science

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Eighty pomelo samples and 80 soil samples were examined using a multielement component test to predict the geographical origins of pomelos produced in 4 regions (Sichuan, Chongqing, Fujian, and Guangxi Provinces) of China. The concentrations of 8 elements were determined by atomic absorption spectrometry. Ca, K, and Na were the most abundant elements. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to reduce the dimensionality of the multielement data from 8 to 2 while retaining the highest possible variance. Using PCA and LDA, 69.66% and 91.30%, respectively, of the pomelo origins were classified correctly using multielement variables, along with 67.06% and 83.40% for soil multielement analysis. Results indicated that the LDA method was more effective for geographical origin classification than PCA. The results of the multielement component test demonstrated its capability to screen pomelo origins rapidly.

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Section: Resultssupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Identification of the Geographical Origins of Pomelos Using Multielement Fingerprinting

Yan

Liu

Xiong

et al. 2015

Journal of Food Science

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“…An elemental fingerprint analysis could serve as a descriptor of the geographical origin, and has the potential to enable authentication of organic crops (Kelly & Bateman, 2010). It was used, for example, in classification of winter wheat, spring barley, faba bean and potato (Laursen et al, 2011), honeys (Chua, Abdul-Rahaman, Sarmidi, & Aziz, 2012), virgin olive oils, pumpkin seed oils, wines and Chinese cabbage (Bandoniene, Zettl, Meisel, & Maneiko, 2013;Benincasa, Lewis, Perri, Sindona, & Tagarelli, 2007;Bong et al, 2012;Geana et al, 2013), onion cultivars based on mineral content (Chope & Terry, 2009;Galdón, González, Rodríguez, & Romero, 2008), and fruit and vegetables (Patras et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

An elemental analysis of conventionally, organically and self-grown carrots

et al. 2016

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“…Furthermore, radiogenic isotope ratios such as 87 Sr/ 86 Sr have been widely used in geographical discrimination studies. Radiogenic isotopes have an advantage over light stable isotopes in that they do not exhibit measurable fractionation during soil formation and plant physiological processes, so their ratios reflect only the geochemical characteristics of the rocks and soils from which they were derived (Degryse et al 2010;Lee et al 2011;Techer et al 2011;Bong et al 2012b). For example, Lee et al (2011) examined the geographical origin of ginsengs grown in South Korea and China using 87 Sr/ 86 Sr ratios, and concluded that their 87 Sr/ 86 Sr ratios reflect the lithological characteristics of the cultivation areas.…”

Section: Introductionmentioning

confidence: 99%

Effects of bedrock on the chemical and Sr isotopic compositions of plants

et al. 2015

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This study was conducted to investigate the relationship between the chemical and isotopic compositions of plants and the lithology of their growth location. This relationship is one of the principles underlying the geographical discrimination used for agricultural, forestry, and food products. Locations in South Korea with solely basaltic (Jeju), granitic (Gongju), and carbonate (Yeongwol) rocks were selected as test sites, and bedrocks, soils, and plants in each location were sampled. The multi-element compositions and Sr isotope ratios ( 87 Sr/ 86 Sr) were analyzed for all samples, including various soil fractions (exchangeable, carbonates, silicates) and plant parts (tree leaves, vegetable leaves, and fruits). Based on a preliminary statistical analysis (ANOVA), Ca, Mg, K, Al, Sr concentrations, and 87 Sr/ 86 Sr ratios were selected as key variables with greater variability with location. Using these variables, a multivariate statistical analysis was conducted, and three soil fractions and plant parts were successfully discriminated according to their geographical origin (i.e., bedrock type) with statistical significance. The results indicated that Sr isotope ratios of bedrocks can be preserved in soils (except in silicate fractions) and plants throughout weathering and plant physiological processes, and are the most critical variable in the tracing of bedrock characteristics.

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Determining the geographical origin of Chinese cabbages using multielement composition and strontium isotope ratio analyses

Cited by 62 publications

References 27 publications

Identification of the Geographical Origins of Pomelos Using Multielement Fingerprinting

Identification of the Geographical Origins of Pomelos Using Multielement Fingerprinting

An elemental analysis of conventionally, organically and self-grown carrots

Effects of bedrock on the chemical and Sr isotopic compositions of plants

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